Information processing device, information processing method and program

Abstract

To more efficiently evaluate constraint used to create a plan about a movable body.SOLUTION: An information processing device is provided with a processing part. The processing part creates a graph including a plurality of nodes corresponding to a plurality of movable bodies and a plurality of edges representing constraint about at least a part of an arrival order representing an order in which the movable bodies arrive at an object area including a plurality of stop sections at which the movable bodies can stop, a departure order representing an order in which the movable body depart from the object area, and an entering / leaving method as a method for entering the stop sections and leaving from the stop section, on the basis of movable body information including the arrival order and the departure order about each of the plurality of movable bodies, and section information including the entering / leaving method for each of the plurality of stop sections. The processing part selects an evaluation method to be used for graph evaluation among a plurality of evaluation methods on the basis of the section information. The processing part uses the selected evaluation method to evaluate the graph.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] An embodiment of the present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Many of the depots and stations owned by railway operators have tracks where multiple train sets are stopped (parked) in a vertical line on the same track, due to capacity considerations. Such track platforms impose constraints on the order in which train sets enter and exit (hereafter referred to as "parking constraints"). If the parking constraints cannot be met, shunting operations are required to move train sets that are obstructing entry and exit to other track platforms. The entry and exit order is determined by a plan (such as a rolling stock operation plan) created in advance. Because shunting operations require human and time costs, it is desirable to create a plan that satisfies the parking constraints as much as possible. Furthermore, when creating a plan, it is desirable to be able to search more efficiently (for example, quickly) for an optimal or sub-optimal solution that satisfies the parking constraints. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 4241584 [Patent Document 2] Patent No. 5449107 [Patent Document 3] Patent No. 7414705 [Patent Document 4] Japanese Patent Application Publication No. 2023-101286 Summary of the Invention [Problem to be solved by the invention]

[0004] An object of the present invention is to provide an information processing device, an information processing method, and a program that can more efficiently evaluate constraints used in creating a plan for a moving object. [Means for solving the problem]

[0005] An information processing device according to an embodiment includes a processing unit. The processing unit creates a graph including a plurality of nodes corresponding to the plurality of moving objects and a plurality of edges representing constraints on at least some of the arrival order, departure order, and entry / exit method, based on moving object information including, for each of the plurality of moving objects, an arrival order indicating the order in which the moving objects will arrive at a target area including a plurality of stop sections where the moving objects can stop, and a departure order indicating the order in which the moving objects will depart from the target area, and section information including, for each of the plurality of stop sections, an entry / exit method which is a method for entering and exiting the stop section. The processing unit selects, from a plurality of evaluation methods, an evaluation method to be used for evaluating the graph. The processing unit evaluates the graph using the selected evaluation method. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 is a block diagram of an information processing apparatus according to a first embodiment. [Figure 2] FIG. 2 is a diagram showing an example of a data structure of mobile object information. [Figure 3] FIG. 4 is a diagram showing an example of a data structure of section information. [Figure 4] 10 is a flowchart of a graph evaluation process according to the first embodiment. [Figure 5] FIG. 10 is a diagram for explaining an example of an evaluation result. [Figure 6] FIG. 10 is a block diagram of an information processing apparatus according to a second embodiment. [Figure 7] 10 is a flowchart showing an example of a placement plan creation process according to the second embodiment. [Figure 8] FIG. 10 is a block diagram of an information processing apparatus according to a third embodiment. [Figure 9] 11 is a flowchart of a rolling stock scheduling process according to the third embodiment. [Figure 10] FIG. 1 is a hardware configuration diagram of an information processing apparatus according to first to third embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0007] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of an information processing apparatus according to the present invention will be described in detail below with reference to the accompanying drawings.

[0008] In the following, an example in which the moving body is a train of rail cars will be mainly described. However, the moving body is not limited to a train, and may be any other moving body such as a bus, a ship, a robot, an AGV (Automatic Guided Vehicle), or transportation equipment.

[0009] The meanings of the terms used in the following explanation are as follows. · Detention: To stop formation. Track number: A stopping section where trains can be parked. Target area: An area that includes multiple track platforms. For example, a train depot and a station are target areas. · Detention constraints: Constraints on detention for track platforms. - Storage plan: A plan for storing trains on tracks. Operation: The movement of a train from the start of its movement to the end of its movement. Rolling stock operation plan: A plan for the operation, maintenance, and storage of train sets. Maintenance work includes, for example, inspection and / or cleaning. Creating a rolling stock operation plan may also include creating a storage plan.

[0010] An operation can also be interpreted as equivalent to a schedule (operation schedule) in which a train diagram that defines the schedules for multiple train sets is divided by train set unit. An operation can include an operation equivalent to a full-day commercial operation, and an operation equivalent to a commercial operation for less than a day, such as in the morning. Multiple operations that are less than a day can be combined and assigned to one train set as a daily operation. In the following embodiments, an operation is defined in units of one day. For example, when multiple operations that are less than a day are assigned to one train set, the multiple operations are counted together as one operation. The unit of operation is not limited to one day, and the same procedure can be applied to any other unit. In the following embodiments, an operation also includes a train set that is not moved but is kept in a depot or the like all day.

[0011] When a train enters a track in the target area, stops (parks), and then exits, other trains parked on the same track may obstruct its movement, depending on the relationship between the time of entry and the time of exit. It is desirable to create storage plans and vehicle operation plans that minimize shunting work that involves moving obstructing trains.

[0012] In the following, approaching may be referred to as entering or arriving, and leaving may be referred to as leaving or departing. For example, the arrival time of a train set arriving at a target area (a track number included in the target area) may also be referred to as entering time. The departure time of a train set departing from a target area (a track number included in the target area) may also be referred to as leaving time. In the following, the target area may also be referred to as location. For example, the target area where a train enters may be referred to as entering location, and the target area where a train leaves may be referred to as leaving location.

[0013] From the time a train finishes its run until the start of the next day's operation, the train is kept in a track number in the area in question (a depot, station, etc.). Creating a storage plan involves assigning a track number to each train. By not assigning potentially disruptive trains to the same track number, shunting work can be reduced. Creating a rolling stock operation plan involves defining the operation, maintenance work, and shunting work (storage plan) of each train. Unless there is a disruption to the timetable, trains are kept in storage according to the assigned entry and departure times of their assigned runs. Therefore, the degree to which shunting work is reduced also depends on the rolling stock operation plan.

[0014] As a technique for creating a placement plan, for example, a technique for creating a placement plan based on constraint logic programming (Comparative Example 1) has been proposed. Constraint logic programming is a general-purpose method for searching for a constraint satisfaction solution.

[0015] As a technology for creating storage plans and rolling stock operation plans, for example, a technology for creating storage plans and rolling stock operation plans based on mixed integer linear programming (Comparative Example 2) has been proposed. With this technology, by taking storage constraints into consideration, it is possible to create a rolling stock operation plan that minimizes the need for shunting work, and to simultaneously optimize the storage plan and rolling stock operation plan. Mixed integer programming is a general-purpose method for searching for an optimal solution.

[0016] Comparative Examples 1 and 2 use general-purpose methods, which may require time for evaluating constraints, making it difficult to incorporate them into heuristic methods that require large-scale problems and multiple evaluations.

[0017] The following embodiments enable more efficient evaluation of constraints used in creating plans for moving objects. An information processing device of a first embodiment is a device (storage constraint evaluation device) equipped with a function for evaluating storage constraints (storage constraint evaluation). An information processing device of a second embodiment is a device (storage plan creation device) that creates a storage plan based on storage constraint evaluation. An information processing device of a third embodiment is a device (storage plan creation device) that creates a vehicle operation plan (operation cycle that forms the basis of the vehicle operation plan) by a heuristic method that uses storage constraint evaluation as one of the evaluation indexes.

[0018] (First embodiment) The information processing device (depot constraint evaluation device) of the first embodiment creates a graph that reflects the relationship between train sets that hinder movement, and evaluates the degree of suppression of shunting work based on the created graph.

[0019] 1 is a block diagram showing an example of the configuration of an information processing device 100 according to the first embodiment. As shown in FIG. 1, the information processing device 100 includes a storage unit 120, a placement constraint evaluation unit 110, and an output control unit 101.

[0020] The storage unit 120 stores various types of information used by the information processing device 100. For example, the storage unit 120 stores mobile object information 121 and section information 122.

[0021] The mobile unit information 121 is information that includes, for each of a plurality of train sets, at least an arrival order indicating the order in which the train sets will arrive at a target area, and a departure order indicating the order in which the train sets will depart from the target area. The arrival order may be expressed in any format as long as the arrival order can be specified, and may be expressed, for example, as the arrival time (depot entry time). Similarly, the departure order may be expressed in any format as long as the departure order can be specified, and may be expressed, for example, as the departure time (depot departure time). The following mainly describes an example in which the arrival time and departure time are used as the arrival order and departure order, respectively. The mobile unit information 121 can also be interpreted as information that determines the operation schedule (operation schedule) for each of a plurality of train sets.

[0022] Fig. 2 is a diagram showing an example of the data structure of the mobile object information 121. As shown in Fig. 2, the mobile object information 121 includes a train formation, an entry time, and a departure time. In the train formation column, identification information for identifying each train formation is set.

[0023] The mobile object information 121 is not limited to the example in FIG. 2 and may further include other elements. For example, the mobile object information 121 may include information indicating the length of the train set. The information indicating the length of the train set may be expressed by the number of cars included in the train set (number of cars in the train set). When multiple target areas are targeted, the mobile object information 121 may further include specification information that specifies one of the multiple target areas.

[0024] The section information 122 is information that includes at least the entry / exit method, which is the method of entering and exiting the track, for each of a plurality of track platforms.

[0025] Fig. 3 is a diagram showing an example of the data structure of the section information 122. As shown in Fig. 3, the section information 122 includes a track number and an entry / exit method. The track number column contains identification information that identifies each track number. The entry / exit method indicates the method for entering and exiting a track number.

[0026] The section information 122 is not limited to the example in Fig. 3 and may further include other elements. For example, the section information 122 may further include information indicating the length of each of a plurality of track platforms included in the target area. The information indicating the track platform length may be expressed as the number of train sets that can be stored on the track platform (number of train sets), or the number of cars that can be stored on the track platform (number of train sets). Hereinafter, a track platform on which n number of train sets can be stored is referred to as an n-column track platform.

[0027] The section information 122 may further include the minimum difference in time to enter a track platform (minimum approach difference) and the minimum difference in time to exit a track platform (minimum exit difference). The section information 122 may further include information on the connection relationship between multiple track platforms included in the target area. The connection relationship between track platforms may be information indicating track platform divergences and track platform merging.

[0028] The storage unit 120 can be configured from any commonly used storage medium, such as a flash memory, a memory card, a RAM (Random Access Memory), an HDD (Hard Disk Drive), or an optical disk.

[0029] Some or all of the data (mobile body information 121, section information 122) stored in memory unit 120 may be stored in physically different storage media, or may be stored in different storage areas of the same physically identical storage medium.

[0030] Examples of input / output methods are described below. The input / output methods include, for example, a last in first out (LIFO) method, a first in first out (FIFO) method, and a free method.

[0031] The LIFO system is a last-in, first-out system in which the last train to enter is the first to exit. A track where one end of the track serves as an entrance / exit and the other end is a dead end is a LIFO system. In other words, with the LIFO system, a train can enter through the entrance / exit of the track and exit through the entrance / exit, but cannot enter or exit from the end opposite the entrance / exit.

[0032] The FIFO system is a first-in, first-out system in which the first train to enter is the first to exit. Tracks with one end serving as an entrance and the other as an exit (one-way tracks) are FIFO systems. In other words, with the FIFO system, trains can enter through the entrance of a track, but cannot exit through the entrance, and can exit through the exit, but cannot enter through the exit.

[0033] The FREE system is applicable to tracks where both ends can be entrances and exits. With the FREE system, a train can enter and exit from one of the ends of the track, entrance EA, and from the other end, entrance EB.

[0034] The entry / exit method can also be interpreted as information (directional information) that defines the possible directions of entry into and exit from a track number. Below, we will mainly explain the cases where the entry / exit method is either the LIFO method or the FIFO method.

[0035] The entry and exit method determines the order in which multiple trains enter and leave the depot. If the entry and exit times of a train set conflict with the order, other train sets will be obstructed, and shunting work will be required to move those other train sets to other tracks.

[0036] For example, in a LIFO system, the order in which items are taken out is the reverse of the order in which they are stored. In a FIFO system, the order in which items are taken out is the same as the order in which they are stored.

[0037] For example, if one of a pair of trains has a later arrival time and an earlier departure time, the two trains in the pair can enter and leave the depot without any problems on a LIFO track. Such a pair will be referred to as a LIFO pair below.

[0038] On the other hand, if one of a pair of trains has a later entry time and a later departure time, then in a LIFO track, the train with the later departure time will be kept ahead of the train with the earlier departure time (towards the entrance / exit). Therefore, in the case of a LIFO track, the rear train will have its path towards the entrance / exit blocked by the train in front. This necessitates shunting work for the impeding train in front. In the case of a FIFO track, the two trains in such a pair can enter and leave the depot without any problems. Such pairs will be referred to as FIFO pairs below.

[0039] When multiple trains enter and leave the warehouse in reverse order, it is the same as any pair of trains included in the multiple trains being a LIFO pair. For example, when two trains enter and leave the warehouse in reverse order, it is the same as those two trains being a LIFO pair. When three trains enter and leave the warehouse in reverse order, it is the same as all three pairs of two trains selected from those three trains being LIFO pairs.

[0040] Similarly, when multiple trains are loaded and unloaded in the same order, it is the same as any pair of trains included in the multiple trains being a FIFO pair.

[0041] As mentioned above, shunting operations require both human resources and time. For this reason, it is desirable not to store combinations of trains on the same track if the order of their arrival and departure is contrary to the order determined by the entry and departure method. For example, it is desirable to store combinations of trains in which all pairs are LIFO pairs on a track using the LIFO method.

[0042] When the conversion from the order of entering and leaving the depot to the order determined by the entry and exit method is expressed as a product of interchangeability, the minimum number of interchangeable units corresponds to the number of shunting operations required. Note that one shunting operation means switching one train set to another track and then returning it to the original track. For example, the number of FIFO pairs among the pairs contained in multiple train sets parked on a LIFO system track corresponds to the number of shunting operations.

[0043] Returning to the explanation of Fig. 1, the retention constraint evaluation unit 110 evaluates retention constraints. The retention constraint evaluation unit 110 includes a graph creation unit 111, a selection unit 112, and a graph evaluation unit 113.

[0044] The graph creation unit 111 creates a graph that reflects the relationships between train sets that hinder movement due to storage, based on the mobile unit information 121 and the section information 122. For example, the graph creation unit 111 creates a graph that includes a plurality of nodes corresponding to a plurality of train sets and a plurality of edges that represent constraints on at least some of the entry time (arrival time), the departure time (departure time), and the entry / exit method, based on the mobile unit information 121 and the section information.

[0045] The constraints that the edges represent include at least some of the following constraints: - Constraints on the difference in arrival time (arrival order) between multiple trains Constraints on the difference in departure times (departure order) between multiple trains - Constraints on whether the entry and exit methods of multiple trains match

[0046] The graph creation unit 111 includes a node creation unit 111a and an edge creation unit 111b.

[0047] The node creation unit 111a creates nodes based on the mobile unit information 121. For example, the node creation unit 111a creates nodes in the same number as the number of train sets. When multiple target areas exist, the node creation unit 111a may create nodes in the same number as the number of train sets that enter and leave the multiple target areas. The node creation unit 111a may create nodes in the same number as the number of train sets that enter and leave the target area for each of the multiple target areas. The node creation unit 111a may create nodes in the same number as the number of train sets that enter and leave one target area (such as a target area identified by the identification information) out of the multiple target areas.

[0048] The node creation unit 111a may create nodes to which weights are set according to the length of the train set. For example, the node creation unit 111a uses the mobile object information 121 including the length of the train set to set the length of the corresponding train set (such as the number of cars in the train set) as a weight for each of the created nodes.

[0049] The edge creation unit 111b creates edges between multiple nodes based on the mobile unit information 121 and the section information 122. For example, the edge creation unit 111b creates edges between nodes corresponding to predetermined pairs of LIFO pairs and FIFO pairs. Such edges correspond to edges that represent constraints on whether the entry and exit methods of multiple train sets match.

[0050] Whether an edge is to be created in a LIFO pair or a FIFO pair may be determined, for example, according to an evaluation method using a graph. For example, the evaluation method may include a method of evaluating nodes with an edge and a method of evaluating nodes without an edge. Therefore, a pair that can be evaluated more efficiently depending on the evaluation method that can be selected may be determined as a pair for creating an edge.

[0051] The edge creating unit 111b may create edges according to other conditions, examples of which are listed below. The condition that the difference in arrival times is greater than or equal to the minimum approach difference (a constraint on the difference in arrival times between multiple trains, a constraint indicating that the difference in arrival times between multiple trains is greater than or equal to the minimum approach difference) The condition that the departure time difference is equal to or greater than the minimum departure difference (a constraint on the difference in departure times between multiple trains, a constraint indicating that the difference in departure times between multiple trains is equal to or greater than the minimum departure difference) The sum of the lengths of the trains (number of cars, etc.) must be less than or equal to the length of the track (stop section, etc.) - The condition that the target area is the same (restrictions on whether the specific information of multiple trains matches)

[0052] The edge creating unit 111b may create a hyperedge that connects three or more nodes (hypergraph).

[0053] The edge creating unit 111b may create an edge to which a weight is set based on at least one of the moving body information 121 and the section information 122. For example, the edge creating unit 111b may create an edge to which the following elements are set as weights: The edge creating unit 111b may create an edge to which a function with two or more elements out of the following elements as arguments is set as weights: Differences in arrival order between multiple trains Differences in departure order between multiple trains The difference between the sum of the lengths of multiple trains (number of cars, etc.) and the length of the stopping section (number of cars, etc.) Difference between the entry time difference and the minimum approach time difference Difference between departure time difference and minimum departure time difference

[0054] For example, the edge creation unit 111b creates an edge in which the weight is set to the weighted sum of the arrival time difference between multiple train formations and the value obtained by multiplying the departure time difference by "-1". When emphasis is placed on robustness against timetable disruptions, the weighting coefficient for the arrival time difference may be set to a value greater than the weighting coefficient for the value obtained by multiplying the departure time difference by "-1" (for example, the former may be set to 2 and the latter to 1). Note that the reason for multiplying by "-1" is that the larger the value, the smaller the contribution to the weight. The method for reducing the contribution is not limited to multiplying by "-1" and any other method may be used. For example, a method of calculating the reciprocal of a value may be used.

[0055] The graph creation unit 111 may create one graph for one or more target areas, or may create one graph for each of one or more target areas.

[0056] The selection unit 112 selects an evaluation method to be used for evaluating the created graph from among the multiple evaluation methods, based on the section information 122. For example, the selection unit 112 selects an evaluation method determined according to the input / output method included in the section information 122 from among the multiple evaluation methods.

[0057] For example, if multiple tracks within the target area are each 2-column tracks using the LIFO system, assigning a LIFO pair to each track will eliminate the need for shunting work. Therefore, the degree to which shunting work can be reduced can be evaluated by counting the number of LIFO pairs without overlapping train formations (hereinafter referred to as the number of LIFO pairs). If the number of LIFO pairs is equal to or greater than the number of 2-column tracks, shunting work will be unnecessary. If the number of LIFO pairs is less than the number of 2-column tracks, shunting work will be required the number of times equal to the difference (the number of 2-column tracks minus the number of LIFO pairs).

[0058] Counting the number of LIFO pairs without overlapping formations is equivalent to calculating the maximum number of matchings in a graph that has edges between nodes corresponding to LIFO pairs. In graph theory, a matching is a set of edges that do not share nodes. A maximum matching is the largest set of edges that do not share nodes. The Edmonds Algorithm is known as an algorithm for solving the problem of finding a maximum matching (maximum matching problem). By using such an algorithm, it is possible to accurately and quickly evaluate the degree of reduction in shunting work. Note that the evaluation method (algorithm) does not need to be able to calculate an exact solution, and a method that calculates an approximate solution may also be used.

[0059] For example, the selection unit 112 selects an evaluation method for calculating the maximum number of matches using the Edmonds algorithm or the like as an evaluation method for a two-column line in the LIFO method. Note that the algorithm for calculating the maximum number of matches is not limited to the Edmonds algorithm, and any other algorithm may be used. Also, although the LIFO method and LIFO pair have been used as examples, the same procedure can be applied by replacing the LIFO method and LIFO pair with the FIFO method and FIFO pair, respectively. The same applies to the following explanation.

[0060] If the multiple tracks included in the target area are all 3-row tracks using the FIFO system, then shunting work will be unnecessary if three trainsets are assigned to each track, whichever pair is chosen. Therefore, the degree to which shunting work is reduced can be evaluated by, for example, finding the maximum number of triangular subgraphs in a graph with edges between nodes corresponding to FIFO pairs.

[0061] The problem of determining the maximum number of subgraphs forming a triangle has been actively studied in fields such as network analysis, and knowledge from this research can be used to select an evaluation method that provides more efficient (e.g., faster) evaluation. For example, the selection unit 112 selects an evaluation method that determines the maximum number of subgraphs forming a triangle as an evaluation method for a 3-column line in a FIFO system. This evaluation method may be a method that determines the maximum number of subgraphs forming a triangle under the condition that nodes can be shared. This is because it is possible to create a plan to select subgraphs from the subgraphs when the maximum number is determined and assign them to a 3-column line without sharing nodes. In other words, the maximum number of subgraphs forming a triangle can be used to evaluate the degree of suppression of shunting work.

[0062] This section explains the case where the number of trains that can be stored on a track is generalized to n. For an n-series track, shunting operations are unnecessary by assigning n trains corresponding to a clique with n nodes on the graph. A clique is a subgraph with an edge between every two nodes (a complete graph). A clique with two nodes is an edge, and a clique with three nodes is a subgraph that forms a triangle. When n is 4 or greater, the degree of reduction in shunting operations can be evaluated, for example, by finding the clique with the largest number of nodes (maximum clique). This is because it is possible to create a plan by selecting n nodes to assign to the n-series track so as to include as many nodes as possible in the maximum clique. When there are multiple n-series tracks with n or greater than 4, the degree of reduction in shunting operations can be evaluated, for example, by finding the minimum number of cliques that cover the graph. This is because it is possible to create a plan by selecting n nodes to assign to the n-series track so as to include as many nodes as possible in one of the cliques that cover the graph as possible, but to avoid including as many nodes as possible in other cliques, particularly those with a large number of nodes, as many times as there are columns.

[0063] In graph theory, various derivative problems related to cliques have been studied, such as the problem of finding a clique with the maximum number of nodes (maximum clique problem) and the problem of covering a graph with as few cliques as possible (minimum clique cover problem), and knowledge from these problems can be used to select an evaluation method that performs evaluation more efficiently (for example, quickly).That is, the selection unit 112 selects, as the evaluation method for the n-column line, an evaluation method that finds the maximum clique included in the graph or an evaluation method that finds a clique that covers the graph.

[0064] The evaluation method may be a method of counting the number of pairs that maximize the sum of edge weights and have no overlapping vehicle formations. For example, the evaluation method may be a method of selecting LIFO pairs that have as large a difference in arrival time as possible and as small a difference in departure time as possible, without overlapping vehicle formations. The problem of finding a match that maximizes the sum of edge weights is sometimes called the maximum weight matching problem. The Edmonds algorithm described above is also known as an algorithm for the maximum weight matching problem.

[0065] The evaluation by the graph evaluation unit 113 is performed for each graph. For example, if multiple graphs are created for multiple target areas, the evaluation is performed for each of the multiple graphs. Therefore, the selection unit 112 selects an evaluation method for each graph. Furthermore, one target area may include track numbers with multiple types of entry / exit methods (LIFO and FIFO) and track numbers with multiple lengths (e.g., two-column and three-column). In such cases, the selection unit 112 selects an evaluation method corresponding to one type of entry / exit method using the above procedure. For the subgraphs remaining after the evaluation using the selected evaluation method, the selection unit 112 selects an evaluation method corresponding to another type of entry / exit method using the above procedure. The remaining subgraphs are, for example, subgraphs excluding edges included in the selected clique. The above procedure may be repeated with a different selected clique.

[0066] Graph evaluation unit 113 evaluates the graph created by graph creation unit 111 using the evaluation method selected by selection unit 112. For example, graph evaluation unit 113 evaluates the graph by finding the number of one or more cliques included in the graph. When n is 2, graph evaluation unit 113 evaluates the graph by calculating the maximum matching number. When n is 3, graph evaluation unit 113 evaluates the graph by calculating the maximum number of subgraphs that form a triangle. When n is 4 or greater, graph evaluation unit 113 evaluates the graph by finding the maximum clique or the minimum number of cliques when covering the graph.

[0067] The evaluation result by the graph evaluation unit 113 may be in any format, but may be at least a part of the following information, for example. The number of cliques found (e.g., the maximum number of matchings) Information indicating the organization of nodes included in one or more cliques when the number of cliques is calculated

[0068] The output control unit 101 controls the output of various types of information used in the information processing device 100. For example, the output control unit 101 outputs the evaluation results obtained by the graph evaluation unit 113. Any method for outputting information may be used, and examples of applicable methods include displaying the information on a display device and transmitting the information to an external device via a network.

[0069] At least a part of each of the above units (the placement constraint evaluation unit 110, the output control unit 101) may be realized by one or more processing units. Each of the above units is realized, for example, by one or more processors. For example, each of the above units may be realized by having a processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) execute a program, that is, by software. Each of the above units may be realized by a processor such as a dedicated IC (Integrated Circuit), that is, by hardware. Each of the above units may be realized by a combination of software and hardware. When multiple processors are used, each processor may realize one of the units, or may realize two or more of the units.

[0070] The information processing device 100 may be physically configured as one device or may be physically configured as multiple devices. For example, the information processing device 100 may be built in a cloud environment. Furthermore, each unit within the information processing device 100 may be distributed across multiple devices.

[0071] Next, a description will be given of graph evaluation processing by the information processing apparatus 100 of the first embodiment. Fig. 4 is a flowchart showing an example of graph evaluation processing in the first embodiment.

[0072] The node creating unit 111a of the graph creating unit 111 creates a node based on the input moving object information 121 (step S101). The node creating unit 111a may create a node in which the length of the train set is set as a weight.

[0073] The edge creating unit 111b of the graph creating unit 111 creates edges between a plurality of nodes according to conditions (step S102). The edge creating unit 111b may create edges to which weights are set.

[0074] The selection unit 112 selects, from among a plurality of evaluation methods, an evaluation method to be used for evaluating the created graph, based on the section information 122 (step S103).

[0075] The graph evaluation unit 113 evaluates the graph created by the graph creation unit 111 using the evaluation method selected by the selection unit 112 (step S104). The evaluation result by the graph evaluation unit 113 may be output by the output control unit 101.

[0076] FIG. 5 is a diagram for explaining an example of the evaluation results. The circles in the graph in FIG. 5 correspond to six nodes corresponding to six train formations. A line connecting two nodes corresponds to an edge. For example, an edge is created between two nodes that form a LIFO pair.

[0077] The two pairs 501 correspond to pairs (for example, LIFO pairs) found by calculating the maximum number of matches. No replacement work is required for the pair 501. On the other hand, the pair 502 including the remaining node corresponds to a pair that requires replacement work.

[0078] In this way, the information processing device of the first embodiment creates a graph that reflects the relationships between train sets that hinder movement, and evaluates the degree of suppression of shunting work based on the created graph.Even in large-scale problems with a large number of target train sets, it becomes possible to more efficiently (e.g., more quickly) evaluate the degree to which shunting work should be suppressed as much as possible and the method of storage that suppresses shunting work as much as possible.

[0079] (Second embodiment) The information processing device of the second embodiment creates a placement plan based on the placement constraint evaluation by the method of the first embodiment.

[0080] Fig. 6 is a block diagram showing an example of the configuration of an information processing device 100-2 according to the second embodiment. As shown in Fig. 6, the information processing device 100-2 includes a storage unit 120-2, a placement constraint evaluation unit 110, a plan creation unit 130-2, and an output control unit 101-2.

[0081] The second embodiment differs from the first embodiment in that it adds the functions of a storage unit 120-2 and an output control unit 101-2, and a plan creation unit 130-2. The other configurations and functions are the same as those of the information processing device 100 of the first embodiment in FIG. 1, which is a block diagram of the information processing device 100, and therefore the same reference numerals are used and the description thereof will be omitted here.

[0082] The storage unit 120-2 differs from the storage unit 120 of the first embodiment in that it further stores condition information 123-2. The condition information 123-2 includes conditions used when creating a storage plan. The conditions are, for example, the movement route of the crew. The movement route of the crew is, for example, the route that the crew moves from the crew station (waiting area) to the platform.

[0083] The plan creation unit 130-2 creates a storage plan based on the evaluation result of the graph evaluation unit 113. For example, the plan creation unit 130-2 creates a storage plan indicating that a plurality of train sets corresponding to a plurality of nodes included in one or more cliques (edges, triangular subgraphs, etc.) when the number of cliques is calculated are to be stopped in any one of a plurality of stop sections.

[0084] The plan creation unit 130-2 may create a storage plan taking into consideration the condition information 123-2. For example, the plan creation unit 130-2 creates a storage plan indicating that a plurality of train sets, including a train set with an earlier departure order, are to be stopped in order from a stopping section that is closest to a crew member's movement route among a plurality of stopping sections.

[0085] The output control unit 101-2 differs from the output control unit 101 of the first embodiment in that it further outputs information related to the created placement plan.

[0086] In the following, all trains will be described as having the same number of cars, but the same procedures can be applied even if the number of cars varies depending on the train. Also, in the following, all track platforms will be described as having a LIFO entry / exit system, but the same procedures can be applied to other entry / exit systems. Also, in the following, all track platforms will be described as having a 1-column or 2-column system, but the same procedures can be applied to tracks that can accommodate three or more trains.

[0087] The number of two column tracks is T2. The storage plan is created by selecting T2 pairs of train sets without overlapping and assigning them to column track 2, and assigning the remaining train sets to column track 1 without any omissions. In this case, by selecting LIFO pairs as much as possible for the train set pairs assigned to column track 2, the number of shunting operations can be reduced. In addition, by selecting pairs of train sets with as large a difference in their entry times as possible, the increase in shunting operations can be suppressed even if the difference in entry times fluctuates slightly, making the system more robust against timetable disruptions. By selecting pairs of train sets with as small a difference in their departure times as possible and assigning pairs of train sets with the earliest departure times to tracks closest to the crew's station, train sets that are parked on the crew's route from the station to the train they are assigned to will be given priority for departure, reducing the time the crew spends detouring around train sets and improving work efficiency.

[0088] Next, a placement plan creation process by the information processing device 100-2 of the second embodiment will be described with reference to Fig. 7. Fig. 7 is a flowchart showing an example of the placement plan creation process in the second embodiment.

[0089] Steps S201 to S204 are the same as steps S101 to S104 in the information processing apparatus 100 of the first embodiment, and therefore a description thereof will be omitted.

[0090] The plan creation unit 130-2 creates a storage plan using the graph evaluation result and the crew movement route (step S205).

[0091] A specific example of the placement plan creation process will be described.

[0092] In step S203, the selection unit 112 selects an evaluation method for obtaining only T2 pairs of formations that are assigned to two vertical line numbers in, for example, the LIFO method, with as large a difference in storage times as possible and as small a difference in shipping times as possible, without duplication of formations. For example, the selection unit 112 selects the Edmonds Algorithm, which is an algorithm for the maximum weight matching problem, as the evaluation method.

[0093] In step S204, the graph evaluation unit 113 applies the evaluation method selected by the selection unit 112 to evaluate the created graph. In step S205, the plan generation unit 130-2 creates a detention plan based on the evaluation result. Suppose that T2' matchings are obtained by the evaluation.

[0094] When T2' ≥ T2, the plan generation unit 130-2 selects T2 edges in order from the edges with large weights among the T2' matchings (edges), and for each of the selected edges, assigns the pair of formations corresponding to the nodes at both ends of the edge to two vertical line numbers. At this time, the plan generation unit 130-2 assigns the pairs of formations with earlier shipping times to the two vertical line numbers closer to the crew assembly area in order. For the remaining formations, the plan generation unit 130-2 assigns them to the one vertical line number closer to the crew assembly area in order from the formation with the earliest shipping time.

[0095] When T2' < T2, the plan generation unit 130-2 assigns the pairs of formations corresponding to the T2' matchings (edges) to the two vertical line numbers closer to the crew assembly area in order from the formation with the earliest shipping time. The plan generation unit 130-2 appropriately creates (T2 - T2') pairs of formations from the remaining formations such that the difference in shipping times is at least the minimum value of the difference in progress times. The plan generation unit 130-2 assigns the created pairs to the remaining two vertical line numbers in order from the one closer to the crew assembly area. The plan generation unit 130-2 further assigns the remaining formations to the one vertical line number closer to the crew assembly area in order from the formation with the earliest shipping time. The necessary replacement operations at this time are (T2 - T2') times.

[0096] As a result, it is possible to create a storage plan that minimizes shunting work, is robust against timetable disruptions, and reduces the travel time of crew members.

[0097] The output control unit 101-2 outputs information based on the storage plan created by the plan creation unit 130-2, for example, the created storage plan and the number of shunting operations.

[0098] In this way, in the second embodiment, even in the case of a large-scale problem involving a large number of target trains, it is possible to minimize shunting operations and create a storage plan more efficiently (e.g., more quickly) that takes into account the impact of timetable disruptions and the work efficiency of crew members.

[0099] (Third embodiment) The information processing device of the third embodiment creates a vehicle operation plan by a heuristic method using a parking constraint evaluation as one of the evaluation indexes.

[0100] Fig. 8 is a block diagram showing an example of the configuration of an information processing device 100-3 according to the third embodiment. As shown in Fig. 8, the information processing device 100-3 includes a storage unit 120-3, an evaluation unit 140-3, a plan creation unit 130-3, and an output control unit 101-3.

[0101] The third embodiment differs from the second embodiment in that it adds the functions of a storage unit 120-3, a plan creation unit 130-3, and an output control unit 101-3, and an evaluation unit 140-3. The other configurations and functions are the same as those of the information processing device 100-2 of the second embodiment in FIG. 6, which is a block diagram of the information processing device 100-2 of the second embodiment, and therefore the same reference numerals are used and the description thereof will be omitted here.

[0102] The storage unit 120-3 stores condition information 123-3 that further includes conditions used when creating a rolling stock scheduling. The conditions used when creating a rolling stock scheduling include, for example, at least some of the following operating conditions. Areas and times when maintenance work can be performed Target number of out-of-service trips Legal maintenance cycle Target maintenance intervals Target variance of maintenance intervals Target period for external placement Target value for variance of external placement interval Target number of combinations of trains that can be stored on a vertical track Weighting coefficient for the type of train operation (schedule) -Weighting coefficient for train schedule changes -Weighting coefficient for evaluation value of vehicle operation plan

[0103] The conditions used when creating a rolling stock operation plan may further include the following conditions. Information on updating candidate vehicle operation plans (update conditions) Information about termination conditions

[0104] Note that "outside storage" refers to storing a train in an area (such as a station) where maintenance work cannot be performed. Operational circulation is the allocation pattern of operations assigned to a train set.

[0105] The plan creation unit 130-3 creates a vehicle scheduling plan including a storage plan. For example, the plan creation unit 130-3 creates a vehicle scheduling plan in the form of an operation rotation. In this embodiment, a vehicle scheduling plan is created by changing a candidate for operation rotation and evaluating the changed candidate (change candidate). The plan creation unit 130-3 includes a candidate creation unit 131-3, an update unit 132-3, and a determination unit 133-3.

[0106] The candidate creation unit 131-3 executes a process for creating a change candidate by changing a part of a candidate for a vehicle scheduling plan for a plurality of formations. For example, the candidate creation unit 131-3 creates a change candidate by rearranging the order of a part of a plurality of operations (operation schedules) included in the candidate. The candidate creation unit 131-3 may create a plurality of change candidates by changing one candidate.

[0107] The evaluation unit 140-3 executes a process of calculating an evaluation value for the created change candidate, which represents the degree to which one or more operational conditions for a plurality of formations are satisfied. The evaluation value includes the evaluation result of the graph. Therefore, the evaluation unit 140-3 includes the same retention constraint evaluation unit 110 as in the first and second embodiments, which outputs the evaluation result of the graph. As will be described later, the evaluation unit 140-3 may calculate one or more evaluation values ​​including evaluation values ​​other than those corresponding to the evaluation result of the graph.

[0108] If the evaluation value calculated by the evaluation unit 140-3 satisfies the update condition, the update unit 132-3 executes an update process to update the candidate with a change candidate.

[0109] The determination unit 133-3 determines whether or not a termination condition, which indicates a condition for terminating the repetition of the creation process, calculation process, and update process, is satisfied.

[0110] For example, the plan creation unit 130-3 repeatedly executes the creation process, calculation process, and update process until a termination condition is satisfied, and outputs the candidate obtained when the termination condition is satisfied.

[0111] The output control unit 101-3 differs from the output control unit 101-2 of the second embodiment in that it outputs information related to the created rolling stock operation plan.

[0112] The procedure for creating a vehicle operation plan will be explained in more detail below. A vehicle operation plan is created by assigning operation, maintenance work, and storage plans to multiple train formations. Below, we will explain in detail the conditions (operation conditions, etc.) used when creating a vehicle operation plan.

[0113] Many lines use multiple types of train schedules, such as a weekday schedule, a Saturday schedule, and a holiday schedule. That is, multiple different types of operation schedules may be defined depending on the day of the week, etc. In such cases, the plan creation unit 130-3 creates a vehicle operation plan so as to assign different operations according to the type of train schedule.

[0114] Maintenance work is sometimes subject to legally mandated cycles, and it is desirable to carry out it regularly. Maintenance work is limited to certain locations (target areas) and times, such as only being carried out during the day at a railroad depot. Therefore, whether or not a train can undergo maintenance work depends on the train's assigned operation.

[0115] For example, suppose that maintenance work requires three hours and can be performed at the depot between 10:00 and 17:00. Suppose that a certain train set L1 is assigned to operation OA, which leaves the depot at 6:00 and returns to the depot at 10:00, and operation OB, which departs the depot at 16:00 and returns to station SA at 23:00. Train set L1 is scheduled to be kept in the depot during the time period and at the location (train set) where maintenance work can be performed, for longer than the required time. Therefore, maintenance work can be performed on train set L1.

[0116] As mentioned above, the number of operations can include spare cars that are kept in a depot or other location all day, so the number of operations matches the number of train sets. Therefore, a train operation plan can be created by assigning one operation per day to each train set without any omissions or overlaps.

[0117] As mentioned above, operations are determined on a daily basis. Therefore, the departure time and departure location of an operation are the time and location of departure at the beginning of the day, and the arrival time and arrival location are the time and location of arrival at the end of the day.

[0118] Let's take the example of train set L1 above. For operation OA', which is assigned to train set L1 on a daily basis, the departure time and departure location are 6:00 and the depot, which are the departure time and departure location of operation OA. Also, for operation OA', the arrival time and arrival location are 23:00 and the station SA, which are the arrival time and arrival location of operation OB.

[0119] If the entry location of the operation assigned to the train set differs from the departure location of the operation assigned the next day, a train must be sent from the entry location to the departure location without passengers. Because sending a train requires human and time costs, it is desirable to create a vehicle operation plan in which the entry and departure locations of consecutive operations match as much as possible. The number of times the entry and departure locations do not match is the number of trips.

[0120] A train that is parked in a location where maintenance work can be performed for longer than the required time during a time period when maintenance work is possible is called a train that can be performed for maintenance work. For example, the above train OA' is a train that can be performed for maintenance work. Since maintenance work needs to be performed periodically, it is desirable to create a vehicle operation plan that periodically allocates trains that can be performed for maintenance work.

[0121] From a safety perspective, it is undesirable for trains to be stored outside in locations where maintenance work cannot be performed (such as stations) for consecutive days, or for such storage to be repeated at short intervals. Trains whose depot location is where maintenance work cannot be performed are referred to as "trains with outside storage," since the assigned train set will be stored outside. For example, train OA', whose depot location is station SA, is a train that will be stored outside. Therefore, it is desirable to create a rolling stock operation plan that allocates trains that will be stored outside at equal intervals.

[0122] The degree to which shunting work is restricted depends on the order in which trains enter (arrival order) and leave (departure order) the target area (vehicle depot, station). Since trains enter the depot at the time of the train assigned to them on the day and leave at the time of the train assigned to them the next day, the degree of shunting work involved in overnight storage is determined by the rolling stock operation plan. Therefore, it is desirable to take storage constraints into account when creating a rolling stock operation plan.

[0123] Furthermore, if there are many storage plans that suppress shunting work to the same extent, it will be possible to reschedule storage plans without increasing shunting work even when a timetable disruption occurs. A large number of equivalent storage plans is expected to exist. For example, when train set L1 is a LIFO pair with both train sets L2 and L3, no shunting work will be required regardless of whether train sets L1 and L2 or L1 and L3 are selected as train set pairs to be stored on the same track. Suppose a storage plan that assigns train sets L1 and L2 to the same track is selected, but train set L2 is delayed due to a timetable disruption, and shunting work will be required if train set L2 is stored as planned. In this case, by rescheduling train sets L3 to be assigned to the same track as train set L1 instead of L2, shunting work will remain unnecessary.

[0124] The number of LIFO pairs is maximum when the ascending order of the trains' entry times matches the descending order of their departure times. In this case, any pair of trains will be a LIFO pair. If the number of trains is N, then a train whose entry order is 1 will have an exit order of N, a train whose entry order is 2 will have an exit order of (N-1), a train whose entry order is 3 will have an exit order of (N-2), and so on. In other words, for all trains, the sum of the entry order value and the exit order value is (1+N).

[0125] It is desirable for rolling stock operation plans to repeat the same pattern as much as possible to prevent human error. Also, since there are various conditions for train formations depending on the distance traveled, it is desirable for them to be used evenly.

[0126] To efficiently create a rolling stock operation plan that satisfies these many conditions, a technique is used to create a draft rolling stock operation plan by creating an operation allocation pattern and shifting the operation of each train set by one day at a time. This pattern corresponds to the operation cycle mentioned above.

[0127] The operation cycle is information that arranges all operations included in the train timetable in a circular sequence. By assigning operations to vehicle units according to the operation cycle, the operation of the vehicle units is patterned, making it possible to create a more understandable vehicle operation plan. In addition, since all operations are assigned evenly to each vehicle unit, with the number of units as a cycle, the running distances of multiple units are equalized.

[0128] Therefore, it is desirable that the operation cycle meets the conditions of the vehicle operation plan. That is, it is desirable that the vehicle operation plan be created taking into consideration the matching of the entrance and exit locations of consecutive operations, the equalization of intervals between operations where maintenance work can be performed, the equalization of intervals between operations that require outside storage, and storage constraints.

[0129] In addition, because operations vary depending on the train schedule, an operation cycle is also created for each train schedule. When creating a vehicle operation plan, for example, a weekday operation cycle is assigned to weekdays, and a holiday operation cycle is assigned to holidays. For example, let's assume that the operation cycles for weekdays, Saturdays, and Sundays are defined as follows: Weekday operation cycle: WD1, WD2, WD3, WD4, ... Saturday operation cycle: Circular permutation of SD1, SD2, SD3, SD4, etc. Holiday operation cycle: Circular permutation of HD1, HD2, HD3, HD4, etc.

[0130] If the operation assigned to a certain vehicle unit on Friday is operation WD1, then operations are assigned according to the order within the permutation while switching the operation cycle according to the train timetable, such as operation SD2 on Saturday, operation HD3 on Sunday, and operation WD4 on Monday. Therefore, it is desirable that the conditions of the vehicle operation plan are not only satisfied independently by each operation cycle, but also when switching between multiple operation cycles.

[0131] For example, the condition that the entrance and departure locations of consecutive services match not only includes the condition that the entrance location of weekday service WD1 and the departure location of weekday service WD2 match, but also the condition that the entrance location of weekday service WD1 and the departure location of Saturday service SD2 match. In other words, it is desirable that the entrance and departure locations of consecutive services match for all switching of the operation cycle, such as from weekday to weekday, from weekday to holiday, holiday to weekday, and holiday to holiday.

[0132] For example, suppose the maintenance work condition is to set the target cycle for maintenance work to once every two days. This condition desirably includes not only the condition that when weekday service WD1 is a service for which maintenance work can be performed, weekday service WD3 is a service for which maintenance work can be performed, but also the condition that holiday service HD3 is a service for which maintenance work can be performed. In other words, it is desirable that whether or not maintenance work can be performed is consistent between weekdays and holidays for services with the same order.

[0133] Similarly, when creating a storage plan included in a vehicle operation plan, multiple operation circulation switches are taken into consideration. For example, to evaluate the degree of suppression of shunting work, it is desirable to take into consideration not only the storage constraints due to input when the day after a weekday is a weekday, but also the storage constraints due to input when the day after a weekday is a Saturday, as shown below. Input when the day after a weekday is a weekday: Train set L1 enters the depot at the time of weekday train WD1 and departs at the time of weekday train WD2, train set L2 enters the depot at the time of weekday train WD2 and departs at the time of weekday train WD3, train set L3 enters the depot at the time of weekday train WD3 and departs at the time of weekday train WD4, ... (the rest is omitted) Input when the day after a weekday is a Saturday: Train set L1 that enters the depot at the time of weekday service WD1 and departs at the time of Saturday service SD2, ... (the rest is omitted)

[0134] That is, it is desirable to evaluate the retention constraint for every switch of the operation cycle and evaluate the operation cycle based on the evaluation value of the retention constraint.

[0135] Furthermore, because trains with different entry locations cannot be stored on the same track, storage constraints must be considered for each entry location. For example, if there are trains that enter (and are stored) at a depot, station SA, and station SB, and only the depot and station SA have tracks (column tracks) for storing multiple trains in a column, storage constraints are considered independently for the train that enters the depot and the train that enters station SA. There is no need to consider storage constraints for trains that enter station SB, which does not have a column track.

[0136] In this embodiment, the information processing device 100-3 uses a heuristic method based on neighborhood search to create an operation cycle that satisfies the various conditions of the vehicle operation plan as much as possible.

[0137] Below, we will explain an example of simultaneously creating three operation cycles for weekdays, Saturdays, and holidays based on three train schedules: weekday schedule, Saturday schedule, and holiday schedule.The same procedure can be applied even if the number of train schedules and operation cycles is other than three.

[0138] There are nine ways to switch train schedules: from weekday to weekday, from weekday to Saturday, from weekday to holiday, from Saturday to weekday, from Saturday to Saturday, from Saturday to holiday, from holiday to weekday, from holiday to Saturday, and from holiday to holiday. Below, we will explain using a typical week as an example. In a typical week, Monday to Friday is the weekday schedule, Saturday is the Saturday schedule, and Sunday is the holiday schedule.

[0139] In a typical week, the number of times each operation cycle is assigned is 5 for weekdays, 1 for Saturdays, and 1 for holidays. In a typical week, the number of times an operation cycle switch occurs is 4 from weekday to weekday, 1 from weekday to Saturday, 1 from Saturday to holiday, and 1 from holiday to weekday, and 0 for all others.

[0140] Next, rolling stock scheduling processing by the information processing device 100-3 according to the third embodiment will be described with reference to Fig. 9. Fig. 9 is a flowchart showing an example of rolling stock scheduling processing according to the third embodiment.

[0141] The candidate creation unit 131-3 creates initial candidates for a vehicle operation plan (operation cycle) (step S301). It is desirable for the candidate creation unit 131-3 to create initial candidates as quickly as possible. For example, the candidate creation unit 131-3 creates, as an initial candidate, an operation cycle in which the order of operations is determined so that the order of entry and exit is the same as the order of entry and exit of multiple train formations determined in the mobile unit information 121 (corresponding to multiple operation schedules). The method of creating initial candidates is not limited to this, and any other method may be used. For example, the candidate creation unit 131-3 may create initial candidates so as to satisfy the following conditions as much as possible. The entry and exit locations of consecutive trips in the same operation cycle are the same. The entry and exit locations of operations with the same sequence of different operational cycles are the same.

[0142] The candidate creation unit 131-3 creates three candidates for the operation cycle: weekdays, Saturdays, and holidays. For example, the candidate creation unit 131-3 sets weekday operation WD1 as the first operation of the weekday operation cycle, and sets the first operation of the Saturday and holiday operation cycle to an operation whose entry and exit locations are preferably the same as those of operation WD1, and sets the second weekday operation to an operation whose exit location is preferably the entry location of operation WD1. The candidate creation unit 131-3 subsequently determines the order of operations sequentially in the same manner.

[0143] The evaluation unit 140-3 calculates an evaluation value for the candidate (step S302). Hereinafter, the smaller the evaluation value, the better the evaluation. For example, the evaluation unit 140-3 calculates one or more evaluation values ​​based on one or more conditions of the vehicle operation plan, and sets the weighted sum of the one or more evaluation values ​​as the evaluation value for the operation rotation candidate.

[0144] Six examples of evaluation values ​​(evaluation values ​​E1 to E6) are described below. Evaluation unit 140-3 may use some of the following six evaluation values, or may use an evaluation value other than the following six evaluation values.

[0145] The evaluation value E1 corresponds to an evaluation value based on the condition that the entrance and departure locations of consecutive trips match. The evaluation value E1 is, for example, a weighted sum of the number of times that the entrance and departure locations of consecutive trips do not match at each switch in the operation cycle. For example, the weight for each switch is the number of times that the switch occurs in a typical week.

[0146] The evaluation value E1 may be calculated taking into account the target value of the number of forwardings. For example, when the number of forwardings is smaller than the target value, the weight is halved. This allows the evaluation to be weighted towards other conditions when the number of forwardings reaches the target value.

[0147] The evaluation value E2 corresponds to an evaluation value based on the condition for equalizing the number of operations in which maintenance work can be performed. The evaluation value E2 is, for example, a weighted sum of the number of times that there is a discrepancy in whether or not maintenance work can be performed for operations in which the order of different operation cycles is the same. There are three combinations of operation cycles, for example, weekdays and Saturdays, Saturdays and holidays, and holidays and weekdays. The weight for each combination is the number of times that combination occurs as a switch in a typical week. Weekdays and Saturdays, Saturdays and holidays, and holidays and weekdays are all 1. The evaluation value E2 may also be an evaluation value based on the difference in the number of operations in which maintenance work can be performed for different train schedules.

[0148] The evaluation value E3 corresponds to an evaluation value based on the equalization of operations in which maintenance work can be performed. The evaluation value E3 is, for example, a weighted sum of the variances of the intervals between operations in which maintenance work can be performed in each operation cycle. The weight for each operation cycle is the number of times that operation cycle is assigned in a typical week. The evaluation value E3 may also be an evaluation value based on a target value for the variance of the intervals between maintenance work.

[0149] The evaluation value E4 corresponds to an evaluation value based on the equalization of operations that result in outside storage. The evaluation value E4 is, for example, a weighted sum of the variances of the intervals of equalization of operations that result in outside storage in each operating cycle. The weights for each operating cycle may be the same as those for the evaluation value E3. The evaluation value E4 may also be an evaluation value based on a target value for the variance of the intervals of outside storage.

[0150] The evaluation value E5 corresponds to an evaluation value based on the suppression of shunting work. For example, the evaluation value E5 is calculated by multiplying the weighted sum of the number of pairs of trains assigned to two LIFO-based column numbering tracks at each changeover of the operational circulation by "-1." This number of pairs is equal to the number of LIFO pairs counted without overlapping of trains. The weight for each changeover is, for example, the number of times that changeover occurs in a typical week.

[0151] The evaluation unit 140-3 first creates a formation corresponding to each switch. For example, assume that the weekday operation cycle is in the order of service WD1, service WD2, service WD3, service WD4, etc. In this case, the formation for a weekday-to-weekday switch is as follows: Train L1 enters the depot at the time of weekday train WD1 and departs at the time of weekday train WD2 Train L2 enters the depot at the time of train WD2 and departs at the time of train WD3 Train L3 enters the depot at the time of train WD3 and departs at the time of train WD4 (Hereafter omitted)

[0152] Next, the storage constraint evaluation unit 110 calculates the number of LIFO pairs, counting the number of overlapping trains for the trains corresponding to each switch. The storage constraint evaluation unit 110 first creates a graph. For example, suppose there is a train service that enters (and is stored in) a depot, station SA, and station SB, and only the depot and station SA have two-column tracks with a LIFO system. In this case, the storage constraint evaluation unit 110 creates a graph for each of the depot and station SA.

[0153] The graph of the vehicle base has nodes for the formation numbers entering the vehicle base and edges corresponding to the LIFO pairs in the formations entering the vehicle base. The graph of station SA is similar. Next, the detention constraint evaluation unit 110 selects an algorithm for the maximum matching problem and applies the selected algorithm to the graphs of the vehicle base and station SA respectively to calculate the maximum matching number.

[0154] The detention constraint evaluation unit 110 uses the sum of the maximum matching number for the vehicle base and the maximum matching number for station SA as the number of pairs in the targeted switching. The detention constraint evaluation unit 110 calculates the weighted sum with the occurrence frequency of the switching in a typical one-week period as the weight for the number of pairs in each switching as the evaluation value E5.

[0155] The evaluation value E5 may be an evaluation value corresponding to the number of double-track lines (T2). For example, the detention constraint evaluation unit 110 calculates different evaluation values E5 according to the magnitude relationship between the double-track line number T2 and the number of pairs T2'. <​​​​​​​​​​The evaluation value E5 corresponds to an evaluation value related to, for example, the maximum number of matchings evaluated by the parking constraint evaluation unit 110. In contrast, the evaluation value E6 corresponds to an evaluation value related only to the number of LIFO pairs. If the number of LIFO pairs is large, even if, for example, a train schedule disruption occurs, it is more likely that a vehicle operation plan that satisfies the operation conditions can be created by changing to another pair. The evaluation value E6 can be used to evaluate candidates from this perspective.

[0159] The evaluation unit 140-3 calculates a weighted sum of the evaluation values ​​E1 to E6. The weights are determined, for example, based on the priority of each condition. The priority may be set in descending order of the evaluation values ​​E1 to E6. For example, the weights may be determined according to the priority, such that the weight of the evaluation value E6 is 1, the weight of the evaluation value E5 is the maximum value that the evaluation value E6 can take, the weight of the evaluation value E4 is the maximum value that the evaluation value E5 can take, and so on. This makes it possible to search for candidates that satisfy the conditions with the highest priority as much as possible.

[0160] The weights may be changed depending on the search process. For example, in the early stage of the search, the evaluation unit 140-3 sets the weights of the evaluation values ​​other than the evaluation value E1 to 0, in the middle stage, sets weights to each of the six evaluation values ​​as described above, and in the later stage, sets weights that have smaller variations depending on the evaluation value than in the middle stage. This allows only the highest priority condition to be considered in the early stage of the search, and as the search progresses, other conditions to be considered in a balanced manner. In other words, candidates can be searched for efficiently according to priority.

[0161] Returning to the description of Fig. 9, the candidate creation unit 131-3 creates one or more change candidates by changing the candidate for operation rotation (step S303). An example of the change candidate creation process will be described below.

[0162] (Example 1) The candidate creation unit 131-3 creates a change candidate by, for example, performing an operation to swap two appropriately selected services on the current candidate. Assume that the candidate weekday operation cycles are in the order of service WD1, service WD2, service WD3, service WD4, ... If service WD1 and service WD3 are selected as two appropriate services, the change candidate weekday operation cycles will be service WD3, service WD2, service WD1, service WD4, ... This can eliminate violations of the conditions of the vehicle operation plan between the two swapped services and the services that precede and follow each of the two services.

[0163] (Example 2) The candidate creation unit 131-3, for example, extracts services included in an appropriate number of consecutive sections, and performs an operation on the current candidate to insert the extracted service between two appropriate services to create a change candidate. Service WD1 and service WD3 are selected as the services that are the start and end points of the extracted section, and the position after service WD4 is selected as the position to insert the extracted service. In this case, the change candidates for the weekday operation cycle are service WD4, service WD1, service WD2, service WD3, ... This can eliminate violations of the vehicle operation plan conditions between the service that is the start point of the extracted section and the service before that service, and between the service that is the end point and the service after that service.

[0164] (Example 3) The candidate creation unit 131-3 may create change candidates by associating multiple operation cycles with the same order of operations and applying the same operation to the corresponding multiple operations. Assume that the candidates for the Saturday operation cycle are in the order of operation SD1, operation SD2, operation SD3, operation SD4, etc., and the candidates for the holiday operation cycle are in the order of operation HD1, operation HD2, operation HD3, operation HD4, etc. For example, an operation to exchange two appropriate operations is applied to three operation cycles simultaneously. Assume also that weekday operations WD1 and WD3 are selected as the two appropriate operations.

[0165] At this time, the candidate creation unit 131-3 exchanges the weekday operation cycle services WD1 and WD3, exchanges the corresponding Saturday operation cycle services SD1 and SD3, and exchanges the corresponding Sunday operation cycle services HD1 and HD3. As a result, the Saturday operation cycle becomes service SD3, service SD2, service SD1, service SD4, ..., and the holiday operation cycle becomes service HD3, service HD2, service HD1, service HD4, ....

[0166] (Example 4) In an example of exchanging two appropriate services, two services may be selected based on the conditions of the vehicle scheduling plan. That is, the candidate creation unit 131-3 may select two services that do not satisfy the operating conditions from multiple services and create a change candidate by swapping the two selected services. For example, the candidate creation unit 131-3 may select two services from services that violate the conditions of the vehicle scheduling plan. The candidate creation unit 131-3 may select two services based on the evaluation value of each service (a value obtained in the process of calculating the evaluation value by the evaluation unit 140-3) based on the conditions of the vehicle scheduling plan.

[0167] For example, the candidate creation unit 131-3 may select two services in descending order of their contribution to the evaluation value E1. As described above, the evaluation value E1 is, for example, a weighted sum of the number of times the entrance and exit locations of consecutive services do not match at each switch of the operation cycle. For example, the evaluation value of weekday service WD2 is a value obtained by adding +4 if its exit location does not match the entrance location of weekday service WD1, +1 if its entry location does not match the entrance location of Sunday service HD1, +4 if its entry location does not match the exit location of weekday service WD3, and +1 if its entry location does not match the exit location of Saturday service SD3. The candidate creation unit 131-3 calculates evaluation values ​​for other services in the same way and selects the two services with the largest evaluation values.

[0168] (Example 5) The candidate creation unit 131-3 may select two services to be swapped according to an evaluation value based on the condition of suppressing shunting work. Such an evaluation value is, for example, the absolute value of the difference (hereinafter referred to as the difference DA) between the sum of the entry order and departure order of consecutive services before and after each switch of operation circulation and (1+N) or the square of the difference DA.

[0169] (Example 6) The candidate creation unit 131-3 may select two services to be exchanged according to a probability distribution. For example, the candidate creation unit 131-3 may select two services according to a uniform random number. The candidate creation unit 131-3 may evaluate each service using an evaluation value of each service based on the conditions of the vehicle operation plan, and select two services according to a probability distribution based on the evaluation results. For example, the candidate creation unit 131-3 selects two services based on a probability distribution in which the probability increases as the evaluation value of the service decreases. For example, the candidate creation unit 131-3 uses a probability distribution in which the probability is the normalized value obtained by dividing the evaluation value of each service by the sum of the evaluation values ​​for each service.

[0170] (Example 7) The candidate creation unit 131-3 may select the section of the operation (starting point operation, ending point operation) extracted in Example 2 above and the position of the operation to be inserted based on the conditions of the vehicle operation plan.

[0171] For example, the candidate creation unit 131-3 calculates the number of times the entrance location and exit location do not match, as an evaluation value, for only the first operation in each switch of the operation cycle, and selects the start operation based on the calculated evaluation value. For example, the evaluation value of the start operation of weekday operation WD2 is increased by +4 if its exit location does not match the entrance location of weekday operation WD1, and increased by +1 if it does not match the entrance location of Sunday operation HD1. Similarly, the evaluation value of the end operation is calculated for only the last operation. For example, the evaluation value of the end operation of weekday operation WD2 is increased by +4 if its entrance location does not match the exit location of weekday operation WD3, and increased by +1 if it does not match the exit location of Saturday operation SD3.

[0172] The position of the service to be inserted is selected based on an evaluation value obtained by counting the number of times the entry location and exit location do not match at each switch of the operation cycle. For example, the evaluation value of the position between weekday service WD1 and service WD2 is +4 if the entry location of service WD1 and the exit location of service WD2 match, +1 if the entry location of service WD1 and the exit location of Saturday service SD2 match, +1 if the entry location of Saturday service SD2 and the exit location of Sunday service HD1 match, and +1 if the entry location of service HD1 and the exit location of service WD2 match. As with the operation of exchanging two services, the candidate creation unit 131-3 may select the section and location of the service with the larger evaluation value, or may select the section and location of the service based on a probability distribution normalized to the evaluation value.

[0173] (Example 8) The candidate creation unit 131-3 may create a change candidate by performing the operations shown in each of the above examples multiple times, or may create a change candidate by combining and performing multiple operations shown in each of the above examples.

[0174] (Example 9) The candidate creating unit 131-3 may change the operation for creating candidates based on a search history such as a history of the evaluation values ​​of the candidates.

[0175] (Example 10) The candidate creation unit 131-3 may separate evaluation values ​​for switching to the same operation cycle and evaluation values ​​for switching to different operation cycles, and change the operation based on the evaluation values. For example, the candidate creation unit 131-3 may determine the type to be targeted for the creation process based on the evaluation values ​​for each of multiple types of operation cycle candidates, and execute the creation process for the determined type of candidate.

[0176] For example, let's say the evaluation based on the evaluation value for switching from weekday to weekday is high, but the evaluation based on the evaluation value for switching from weekday to Saturday and from holiday to weekday is low. In this case, the candidate creation unit 131-3 does not operate the candidates for the weekday operation cycle (does not create a change candidate), but creates a change candidate by operating only the Saturday and holiday operation cycle. For example, let's say the evaluation based on the evaluation value for switching from weekday to Saturday, Saturday to holiday, and holiday to weekday is high, but the evaluation based on the evaluation value for switching from weekday to weekday and holiday to holiday is low. In this case, the candidate creation unit 131-3 matches the same order of operations for the three operation cycles and applies the same operation to each of the three operation cycles to create a change candidate.

[0177] Returning to the description of Fig. 9, the evaluation unit 140-3 calculates the evaluation value of the created conversion candidate (step S304). The evaluation unit 140-3 calculates the evaluation value of the conversion candidate by the same method as in step S302.

[0178] The update unit 132-3 updates the current candidate with the created change candidate (step S305). The update unit 132-3, for example, uses an update condition to determine whether to use the change candidate as a new candidate. The update condition is, for example, a condition indicating that the evaluation value of the change candidate is smaller than the evaluation value of the current candidate. The update unit 132-3 compares the evaluation value of the candidate (the evaluation value calculated in step S302) with the evaluation value of the change candidate (the evaluation value calculated in step S304), and if the evaluation value of the change candidate is smaller, the update unit 132-3 uses the change candidate as a new candidate. When multiple change candidates are created, the update unit 132-3 may use the change candidate with the smallest evaluation value among the multiple change candidates as a new candidate.

[0179] The determination unit 133-3 determines whether or not the termination condition is satisfied (step S306). The termination condition may be any condition, but for example, the following conditions may be used. - The execution time for the vehicle operation plan creation process reaches the upper limit. - The time limit for no candidate updates is reached. The number of created candidates reaches the limit. The evaluation value of the candidate (change candidate) is below the threshold. No forwarding is required (for example, the evaluation value E1, which has the highest priority, becomes 0). A condition that combines some or all of multiple conditions, including the above conditions: For example, a condition that indicates that the number of candidates created after the evaluation value E1 stops changing reaches the upper limit.

[0180] If the termination condition is not satisfied (step S306: No), the process returns to step S303 and is repeated. If the termination condition is satisfied (step S306: Yes), the output control unit 101-3 selects a candidate with a high evaluation (smallest evaluation value) from the candidates created so far, outputs it as a rolling stock scheduling plan (step S307), and ends the rolling stock scheduling plan creation process. The output control unit 101-3 may select multiple candidates. For example, the output control unit 101-3 may select a certain number (e.g., five) of candidates in descending order of evaluation value.

[0181] The output control unit 101-3 may output at least a part of the following information other than the rolling stock operation plan (selected candidate): -Evaluation value of selected candidate (Evaluation value E1~E6) Number of trips Number of shunting operations ·The suitability of LIFO pairs for each train schedule change for each pair of operations -Pair of trains that can be stored in two parallel tracks -Changes in candidate evaluation values, etc. Changes in the mean and variance of the evaluation values ​​of the created candidates

[0182] The evaluation unit 140-3 may evaluate the parking constraints using a method that does not use a graph (for example, a general-purpose evaluation method as in Comparative Example 1 and Comparative Example 2), instead of being equipped with the parking constraint evaluation unit 110 of the first (second) embodiment that uses a graph. Even with this configuration, by using the heuristic method (a method for searching for changed candidates) as described above, it is possible to more efficiently create a vehicle operation plan.

[0183] In this way, the information processing device of the third embodiment can more efficiently (for example, more quickly) create a vehicle operation plan that satisfies the conditions, even when the number of target formations is large and the number of train schedules is large (for example, three or more). The conditions are, for example, to minimize out-of-service trains, to perform outside storage and maintenance work as regularly as possible, to minimize shunting work, to take into account the impact of schedule disruptions, and to satisfy these conditions as much as possible even before and after a change in train schedule.

[0184] As described above, according to the first to third embodiments, constraints used to create a plan for a moving object can be evaluated more efficiently.

[0185] Next, the hardware configuration of the information processing apparatus according to the first to third embodiments will be described with reference to Fig. 10. Fig. 10 is an explanatory diagram showing an example of the hardware configuration of the information processing apparatus according to the first to third embodiments.

[0186] The information processing device of the first to third embodiments includes a control device such as a CPU (Central Processing Unit) 51, a storage device such as a ROM (Read Only Memory) 52 and a RAM (Random Access Memory) 53, a communication I / F 54 that connects to a network and communicates, and a bus 61 that connects each part.

[0187] The programs executed by the information processing apparatuses of the first to third embodiments are provided in advance in the ROM 52 or the like.

[0188] The programs executed by the information processing devices of the first to third embodiments may be configured to be provided as a computer program product by being recorded in an installable or executable file format on a computer-readable recording medium such as a CD-ROM (Compact Disk Read Only Memory), a flexible disk (FD), a CD-R (Compact Disk Recordable), or a DVD (Digital Versatile Disk).

[0189] Furthermore, the programs executed by the information processing apparatuses of the first to third embodiments may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Also, the programs executed by the information processing apparatuses of the first to third embodiments may be provided or distributed via a network such as the Internet.

[0190] The programs executed by the information processing devices of the first to third embodiments can cause a computer to function as each unit of the information processing device described above. In this computer, the CPU 51 can read the programs from a computer-readable storage medium onto a main storage device and execute the programs.

[0191] A configuration example of the embodiment will be described below. (Configuration example 1) a graph including a plurality of nodes corresponding to the plurality of moving bodies and a plurality of edges representing constraints on at least some of the arrival order, the departure order, and the entry / exit method, based on moving body information including, for each of a plurality of moving bodies, an arrival order indicating the order in which the moving bodies will arrive at a target area including a plurality of stop sections where the moving bodies can stop, and a departure order indicating the order in which the moving bodies will depart from the target area, and section information including, for each of the plurality of stop sections, an entry / exit method which is the method for entering the stop section and exiting the stop section; selecting an evaluation method to be used for evaluating the graph from among a plurality of evaluation methods based on the section information; evaluating the graph using the selected evaluation technique; Processing section An information processing device comprising: (Configuration example 2) the mobile object information further includes, for each of the plurality of mobile objects, identification information that identifies one of a plurality of target areas; The processing unit creating the graph including a plurality of the nodes corresponding to a plurality of the mobile units arriving at or departing from the target area identified by the same identifying information; The information processing device according to claim 1. (Configuration example 3) the moving object information further includes, for each of the plurality of moving objects, a length of the moving object; The processing unit creating the graph including the nodes with weights set according to the lengths of the moving objects; 3. The information processing device according to claim 1 or 2. (Configuration example 4) The constraint is: A constraint on the difference in the arrival order between the plurality of moving objects; A constraint on the difference in the departure order between a plurality of the moving objects; a constraint on whether the entry and exit methods of the plurality of moving bodies are consistent; including at least a portion of 4. The information processing device according to claim 1. (Configuration Example 5) the moving object information further includes, for each of the plurality of moving objects, a length of the moving object; the section information further includes, for each of the plurality of stop sections, a length of the stop section; the constraints include a constraint indicating that the sum of lengths of the plurality of moving objects is equal to or less than the length of the stop section; 5. An information processing device according to claim 1. (Configuration Example 6) the mobile object information further includes, for each of the plurality of mobile objects, identification information that identifies one of a plurality of target areas; the constraints include a constraint as to whether the specific information of the plurality of moving bodies matches; 6. An information processing device according to claim 1. (Configuration Example 7) The section information further includes, for each of the plurality of stop sections, an approach minimum difference value that is the minimum value of the difference in time at which the vehicle enters the stop section, and an exit minimum difference value that is the minimum value of the difference in time at which the vehicle exits the stop section, the arrival order is an arrival time at which the mobile object arrives at the target area, the departure order is a departure time at which the moving object departs from the target area; The constraint is: a constraint indicating that the difference in arrival time between the plurality of moving bodies is equal to or greater than the minimum approach difference value, and a constraint indicating that the difference in departure time between the plurality of moving bodies is equal to or greater than the minimum exit difference value, 7. An information processing device according to claim 1. (Configuration Example 8) The processing unit creating the graph including the edges to which weights are set according to at least one of the difference in arrival order between the plurality of moving bodies and the difference in departure order between the plurality of moving bodies; 8. An information processing device according to claim 1. (Configuration Example 9) the moving object information further includes, for each of the plurality of moving objects, a length of the moving object; the section information further includes, for each of the plurality of stop sections, a length of the stop section; The processing unit creating the graph including the edges to which weights are set according to the difference between the sum of the lengths of the plurality of moving bodies and the length of the stop section; 9. An information processing device according to claim 1. (Configuration Example 10) The section information further includes, for each of the plurality of stop sections, an approach difference minimum value representing the minimum value of the difference in time at which the vehicle enters the stop section, and an exit difference minimum value representing the minimum value of the difference in time at which the vehicle exits the stop section, the arrival order is an arrival time at which the mobile object arrives at the target area, the departure order is a departure time at which the moving object departs from the target area; The processing unit creating the graph including the edges to which weights are set according to at least one of the difference between the arrival times of the plurality of moving bodies and the minimum approach difference value, and the difference between the departure times of the plurality of moving bodies and the minimum exit difference value; 10. An information processing device according to claim 1. (Configuration Example 11) The processing unit selecting, from among a plurality of evaluation methods, the evaluation method determined in accordance with the entry / exit method included in the section information; 11. An information processing device according to claim 1. (Configuration Example 12) The processing unit evaluating the graph by determining the number of one or more cliques in the graph; 12. An information processing device according to claim 1. (Configuration Example 13) The processing unit outputting an evaluation result that is at least a part of the number and the mobile objects corresponding to the nodes included in one or more of the cliques when the number is calculated; The information processing device according to claim 12. (Configuration Example 14) The processing unit creating a parking plan indicating that the plurality of moving bodies corresponding to the plurality of nodes included in one or more of the cliques when the number is calculated are to be stopped in any one of the plurality of stopping sections; The information processing device according to claim 12. (Configuration Example 15) The processing unit creating the stationing plan indicating that the plurality of moving bodies, including the moving body with the earliest departure order, are to be stopped in order from the stopping section closest to the crew's movement route among the plurality of stopping sections; 15. The information processing device according to claim 14. (Configuration Example 16) The processing unit Execute a process of creating a candidate change by changing a part of the candidate operation plan of the plurality of moving bodies; Calculating an evaluation value representing the degree to which the change candidate satisfies one or more operational conditions of the plurality of moving bodies, If the evaluation value satisfies an update condition, an update process is performed to update the candidate with the change candidate; determining whether a termination condition is satisfied, the termination condition indicating a condition for terminating the repetition of the creation process, the calculation process, and the update process; repeatedly executing the creation process, the calculation process, and the update process until the termination condition is satisfied, and outputting the candidate obtained when the termination condition is satisfied; The evaluation value includes an evaluation result of the graph. 16. An information processing device according to claim 1. (Configuration Example 17) An information processing method executed by an information processing device, creating a graph including a plurality of nodes corresponding to the plurality of moving bodies and a plurality of edges representing constraints on at least some of the arrival order, departure order, and entry / exit method, based on moving body information including, for each of the plurality of moving bodies, an arrival order representing the order in which the moving bodies arrive at a target area including a plurality of stop sections where the moving bodies can stop, and a departure order representing the order in which the moving bodies depart from the target area, and section information including, for each of the plurality of stop sections, an entry / exit method which is a method for entering the stop section and exiting the stop section; selecting an evaluation method to be used for evaluating the graph from among a plurality of evaluation methods based on the section information; evaluating the graph using the selected evaluation technique; An information processing method including: (Configuration Example 18) On the computer, creating a graph including a plurality of nodes corresponding to the plurality of moving bodies and a plurality of edges representing constraints on at least some of the arrival order, departure order, and entry / exit method, based on moving body information including, for each of the plurality of moving bodies, an arrival order representing the order in which the moving bodies arrive at a target area including a plurality of stop sections where the moving bodies can stop, and a departure order representing the order in which the moving bodies depart from the target area, and section information including, for each of the plurality of stop sections, an entry / exit method which is a method for entering the stop section and exiting the stop section; selecting an evaluation method to be used for evaluating the graph from among a plurality of evaluation methods based on the section information; evaluating the graph using the selected evaluation technique; A program to execute. (Configuration Example 19) Execute a process of creating a candidate change by changing a part of the candidate operation plan of the plurality of moving bodies; Calculating an evaluation value representing the degree to which the change candidate satisfies one or more operational conditions of the plurality of moving bodies, If the evaluation value satisfies an update condition, an update process is performed to update the candidate with the change candidate; determining whether a termination condition is satisfied, the termination condition indicating a condition for terminating the repetition of the creation process, the calculation process, and the update process; repeatedly executing the creation process, the calculation process, and the update process until the termination condition is satisfied, and outputting the candidate obtained when the termination condition is satisfied; Processing section An information processing device comprising: (Configuration Example 20) The processing unit a graph including a plurality of nodes corresponding to the plurality of moving bodies and a plurality of edges representing constraints on at least some of the arrival order, the departure order, and the entry / exit method, based on moving body information including, for each of the plurality of moving bodies, an arrival order indicating the order in which the moving bodies arrive at a target area including a plurality of stop sections where the moving bodies can stop, and a departure order indicating the order in which the moving bodies depart from the target area, and section information including, for each of the plurality of stop sections, an entry / exit method which is a method for entering the stop section and exiting the stop section; selecting an evaluation method to be used for evaluating the graph from among a plurality of evaluation methods based on the section information; evaluating the graph using the selected evaluation technique; The evaluation value includes an evaluation result of the graph. 20. The information processing device according to claim 19. (Configuration Example 21) The candidates include a plurality of operation schedules each including an arrival order indicating an order in which the mobile objects will arrive at a target area including a plurality of stop sections where the mobile objects can stop, and a departure order indicating an order in which the mobile objects will depart from the target area, the processing unit creates the change candidate by rearranging the order of some of the plurality of operation schedules. 21. The information processing device according to claim 19 or 20. (Configuration Example 22) The processing unit selecting two of the operation schedules that do not satisfy the operating conditions from the plurality of operation schedules, and interchanging the two selected operation schedules to create the change candidate; 22. The information processing device according to claim 21. (Configuration Example 23) The processing unit selecting two of the operation schedules using an evaluation value based on the difference between the two operation schedules in consecutive arrival orders and the difference between the two operation schedules in consecutive departure orders, and swapping the two selected operation schedules to create the change candidate; 22. The information processing device according to claim 21. (Configuration Example 24) The processing unit changing a method for modifying a part of the candidates based on a history of the creation process; 24. An information processing device according to any one of claims 19 to 23. (Configuration Example 25) The processing unit Executing the creation process for each of the plurality of types of candidates; 25. An information processing device according to any one of claims 19 to 24. (Configuration Example 26) Each of the plurality of types of candidates includes a plurality of flight schedules in a predetermined order; The processing unit creating the change candidates by changing the operation schedules that correspond to the orders included in each of the plurality of types of candidates; 26. The information processing device according to claim 25. (Configuration Example 27) The processing unit determining a type to be subjected to the creation process based on the evaluation values ​​for each of the plurality of types of candidates, and executing the creation process for the candidates of the determined type; 26. The information processing device according to claim 25.

[0192] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0193] 100, 100-2, 100-3 Information processing device 101, 101-2, 101-3 Output control section 110 Placement Constraint Evaluation Unit 111 Graph Creation Department 111a Node Creation Department 111b Edge Creation Section 112 Selection section 113 Graph Evaluation Unit 120, 120-2, 120-3 Storage section 121 Mobile Information 122 Section Information 123-2 Condition Information 130-2, 130-3 Planning Department 131-3 Candidate Creation Department 132-3 Update section 133-3 Judgment section 140-3 Evaluation Section

Claims

1. a graph including a plurality of nodes corresponding to the plurality of moving bodies and a plurality of edges representing constraints on at least some of the arrival order, the departure order, and the entry / exit method, based on moving body information including, for each of a plurality of moving bodies, an arrival order indicating the order in which the moving bodies will arrive at a target area including a plurality of stop sections where the moving bodies can stop, and a departure order indicating the order in which the moving bodies will depart from the target area, and section information including, for each of the plurality of stop sections, an entry / exit method which is the method for entering the stop section and exiting the stop section; selecting an evaluation method to be used for evaluating the graph from among a plurality of evaluation methods based on the section information; evaluating the graph using the selected evaluation technique; Processing section An information processing device comprising:

2. the mobile object information further includes, for each of the plurality of mobile objects, identification information that identifies one of a plurality of target areas; The processing unit creating the graph including a plurality of the nodes corresponding to a plurality of the mobile units arriving at or departing from the target area identified by the same identifying information; The information processing device according to claim 1 .

3. the moving object information further includes, for each of the plurality of moving objects, a length of the moving object; The processing unit creating the graph including the nodes with weights set according to the lengths of the moving objects; The information processing device according to claim 1 .

4. The constraint is: A constraint on the difference in the arrival order between the plurality of moving objects; A constraint on the difference in the departure order between a plurality of the moving objects; a constraint on whether the entry and exit methods of the plurality of moving bodies are consistent; including at least a portion of The information processing device according to claim 1 .

5. the moving object information further includes, for each of the plurality of moving objects, a length of the moving object; the section information further includes, for each of the plurality of stop sections, a length of the stop section; the constraints include a constraint indicating that the sum of lengths of the plurality of moving objects is equal to or less than the length of the stop section; The information processing device according to claim 1 .

6. the mobile object information further includes, for each of the plurality of mobile objects, identification information that identifies one of a plurality of target areas; the constraints include a constraint as to whether the specific information of the plurality of moving bodies matches; The information processing device according to claim 1 .

7. The section information further includes, for each of the plurality of stop sections, an approach minimum difference value that is the minimum value of the difference in time at which the vehicle enters the stop section, and an exit minimum difference value that is the minimum value of the difference in time at which the vehicle exits the stop section, the arrival order is an arrival time at which the mobile object arrives at the target area, the departure order is a departure time at which the moving object departs from the target area; The constraint is: a constraint indicating that the difference in arrival time between the plurality of moving bodies is equal to or greater than the minimum approach difference value, and a constraint indicating that the difference in departure time between the plurality of moving bodies is equal to or greater than the minimum exit difference value, The information processing device according to claim 1 .

8. The processing unit creating the graph including the edges to which weights are set according to at least one of the difference in arrival order between the plurality of moving bodies and the difference in departure order between the plurality of moving bodies; The information processing device according to claim 1 .

9. the moving object information further includes, for each of the plurality of moving objects, a length of the moving object; the section information further includes, for each of the plurality of stop sections, a length of the stop section; The processing unit creating the graph including the edges to which weights are set according to the difference between the sum of the lengths of the plurality of moving bodies and the length of the stop section; The information processing device according to claim 1 .

10. The section information further includes, for each of the plurality of stop sections, an approach difference minimum value representing the minimum value of the difference in time at which the vehicle enters the stop section, and an exit difference minimum value representing the minimum value of the difference in time at which the vehicle exits the stop section, the arrival order is an arrival time at which the mobile object arrives at the target area, the departure order is a departure time at which the moving object departs from the target area; The processing unit creating the graph including the edges to which weights are set according to at least one of the difference between the arrival times of the plurality of moving bodies and the minimum approach difference value, and the difference between the departure times of the plurality of moving bodies and the minimum exit difference value; The information processing device according to claim 1 .

11. The processing unit selecting, from among a plurality of evaluation methods, the evaluation method determined in accordance with the entry / exit method included in the section information; The information processing device according to claim 1 .

12. The processing unit evaluating the graph by determining the number of one or more cliques in the graph; The information processing device according to claim 1 .

13. The processing unit outputting an evaluation result that is at least a part of the number and the mobile objects corresponding to the nodes included in one or more of the cliques when the number is calculated; The information processing device according to claim 12.

14. The processing unit creating a parking plan indicating that the plurality of moving bodies corresponding to the plurality of nodes included in one or more of the cliques when the number is calculated are to be stopped in any one of the plurality of stopping sections; The information processing device according to claim 12.

15. The processing unit creating the stationing plan indicating that the plurality of moving bodies, including the moving body with the earliest departure order, are to be stopped in order from the stopping section closest to the crew's movement route among the plurality of stopping sections; The information processing device according to claim 14.

16. The processing unit Execute a process of creating a candidate change by changing a part of the candidate operation plan of the plurality of moving bodies; Calculating an evaluation value representing the degree to which the change candidate satisfies one or more operational conditions of the plurality of moving bodies, If the evaluation value satisfies an update condition, an update process is performed to update the candidate with the change candidate; determining whether a termination condition is satisfied, the termination condition indicating a condition for terminating the repetition of the creation process, the calculation process, and the update process; repeatedly executing the creation process, the calculation process, and the update process until the termination condition is satisfied, and outputting the candidate obtained when the termination condition is satisfied; The evaluation value includes an evaluation result of the graph. The information processing device according to claim 1 .

17. An information processing method executed by an information processing device, creating a graph including a plurality of nodes corresponding to the plurality of moving bodies and a plurality of edges representing constraints on at least some of the arrival order, departure order, and entry / exit method, based on moving body information including, for each of the plurality of moving bodies, an arrival order representing the order in which the moving bodies arrive at a target area including a plurality of stop sections where the moving bodies can stop, and a departure order representing the order in which the moving bodies depart from the target area, and section information including, for each of the plurality of stop sections, an entry / exit method which is a method for entering the stop section and exiting the stop section; selecting an evaluation method to be used for evaluating the graph from among a plurality of evaluation methods based on the section information; evaluating the graph using the selected evaluation technique; An information processing method including:

18. On the computer, creating a graph including a plurality of nodes corresponding to the plurality of moving bodies and a plurality of edges representing constraints on at least some of the arrival order, departure order, and entry / exit method, based on moving body information including, for each of the plurality of moving bodies, an arrival order representing the order in which the moving bodies arrive at a target area including a plurality of stop sections where the moving bodies can stop, and a departure order representing the order in which the moving bodies depart from the target area, and section information including, for each of the plurality of stop sections, an entry / exit method which is a method for entering the stop section and exiting the stop section; selecting an evaluation method to be used for evaluating the graph from among a plurality of evaluation methods based on the section information; evaluating the graph using the selected evaluation technique; A program to execute.

19. Execute a process of creating a candidate change by changing a part of the candidate operation plan of the plurality of moving bodies; Calculating an evaluation value representing the degree to which the change candidate satisfies one or more operational conditions of the plurality of moving bodies, If the evaluation value satisfies an update condition, an update process is performed to update the candidate with the change candidate; determining whether a termination condition is satisfied, the termination condition indicating a condition for terminating the repetition of the creation process, the calculation process, and the update process; repeatedly executing the creation process, the calculation process, and the update process until the termination condition is satisfied, and outputting the candidate obtained when the termination condition is satisfied; Processing section An information processing device comprising:

20. The processing unit a graph including a plurality of nodes corresponding to the plurality of moving bodies and a plurality of edges representing constraints on at least some of the arrival order, the departure order, and the entry / exit method, based on moving body information including, for each of the plurality of moving bodies, an arrival order indicating the order in which the moving bodies arrive at a target area including a plurality of stop sections where the moving bodies can stop, and a departure order indicating the order in which the moving bodies depart from the target area, and section information including, for each of the plurality of stop sections, an entry / exit method which is a method for entering the stop section and exiting the stop section; selecting an evaluation method to be used for evaluating the graph from among a plurality of evaluation methods based on the section information; evaluating the graph using the selected evaluation technique; The evaluation value includes an evaluation result of the graph. The information processing device according to claim 19.

21. The candidates include a plurality of operation schedules each including an arrival order indicating an order in which the mobile objects will arrive at a target area including a plurality of stop sections where the mobile objects can stop, and a departure order indicating an order in which the mobile objects will depart from the target area, the processing unit creates the change candidate by rearranging the order of some of the plurality of operation schedules. The information processing device according to claim 19.

22. The processing unit selecting two of the operation schedules that do not satisfy the operating conditions from the plurality of operation schedules, and interchanging the two selected operation schedules to create the change candidate; The information processing device according to claim 21.

23. The processing unit selecting two operation schedules using an evaluation value based on the difference between the two operation schedules in successive arrival orders and the difference between the two operation schedules in successive departure orders, and swapping the two selected operation schedules to create the change candidate; The information processing device according to claim 21.

24. The processing unit changing a method for modifying a part of the candidates based on a history of the creation process; The information processing device according to claim 19.

25. The processing unit Executing the creation process for each of the plurality of types of candidates; The information processing device according to claim 19.

26. Each of the plurality of types of candidates includes a plurality of flight schedules in a predetermined order; The processing unit creating the change candidates by changing the operation schedules that correspond to the orders included in each of the plurality of types of candidates; The information processing device according to claim 25.

27. The processing unit determining a type to be subjected to the creation process based on the evaluation values ​​for each of the plurality of types of candidates, and executing the creation process for the candidates of the determined type; The information processing device according to claim 25.

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