Cooperative compilation method and system for traffic depot in-pipe driving plan and diagram-defined train plan

Abstract

The invention discloses a cooperative compilation method and a cooperative compilation system for a traffic depot in-pipe driving plan and a diagram-defined train plan, and the method comprises the steps: collecting operation data, generating a speed-distance curve which reflects the acceleration, coasting, deceleration and braking processes of the operation data on each selectable path, and calculating the occupied blocking time of each basic unit based on the speed-distance curve; the blocking time and the line information are input into a pre-established mixed integer model together, the model comprises a moving unit operation process constraint, a path selection constraint and a basic unit occupation conflict constraint, and a large M method is adopted to achieve coupling of basic unit entering time and basic unit leaving time. And solving the mixed integer model by using a rolling time domain algorithm in combination with adaptive large-scale neighborhood search and a simulated annealing acceptance strategy to obtain an optimized operation plan of a shunting locomotive and a small-running train, and realizing collaborative compilation of a diagram-defined train plan and shunting and small-running operations in a train service depot. According to the method, the railway transportation resource allocation efficiency and the driving organization coordination are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of train operation optimization, and particularly relates to a method and system for collaborative compilation of train operation plans within the jurisdiction of a train operation depot and the scheduled train plans. Background Art

[0002] In the research of railway transportation organization, traditional train operation plan compilation mainly focuses on train operation dispatching and command, emphasizing the optimization of the scheduled train timetable, while paying insufficient attention to the collaborative effect between the internal train operation management of the train operation depot and the station dispatching. Most existing technologies adopt a modeling method based on the macro railway network, abstracting the railway network as a system composed of each station node and section, and ensuring the safe operation of trains between nodes and sections by setting fixed time parameters (such as running time, interval between stations, etc.). Such methods require trains to select a unique running path between the starting point and the ending point, and strictly limit the driving duration of trains within each section and the residence time within the station, thereby achieving basic operation safety and time management to a certain extent.

[0003] However, this compilation method centered around the scheduled train plan has many deficiencies:

[0004] 1. Disconnection between in-station operations and actual situations

[0005] Existing methods simplify the station as a single node and cannot fully describe the complex operation processes of trains in the station, such as passenger boarding and alighting, train meeting, overtaking, turning back, as well as loading, unloading, breaking up, emptying, etc. This simplification results in the compiled train operation diagram being difficult to reflect the actual operation requirements on-site, affecting resource allocation and dispatching effects.

[0006] 2. Limitations of fixed time parameters

[0007] Some models adopt a fixed minimum interval time to ensure safety, but this approach ignores the differences in the actual interval times required for different operations. When the actual interval is less than the preset fixed value, it is easy to cause waste of line capacity and reduce the overall transportation efficiency.

[0008] 3. Insufficient comprehensive optimization

[0009] Existing research mainly focuses on the optimization of the scheduled train operation diagram. When considering shunting, cross-station operation, small transfer trains, and the dynamic requirements of station operations, there is a lack of comprehensive analysis and coordinated resolution of conflicts between various operations. Although some technologies have refined the description of the station operation process, such as stages of entering the station, occupying the arrival and departure lines, and leaving the station, in actual dispatching, the problems of resource conflicts and mismatched operation times are still difficult to be fundamentally solved.

[0010] With the continuous growth of railway transportation demand, the internal shunting of locomotives across stations, the organization of small-scale train operations, and the increasing dependence of various operations in stations on the train operation plan have made it increasingly difficult to improve the overall coordination of train operation organization and operation efficiency. Therefore, it is particularly important to explore a collaborative compilation mechanism that can not only meet the fixed time requirements of scheduled trains, but also flexibly coordinate the various operational needs within the train operation section. Summary of the invention

[0011] In view of the defects of the prior art, the present invention provides a method for collaboratively compiling the driving plan and the scheduled train plan within the train operation section. The method focuses on the integrated scheduling of driving and shunting, and uses the track-level occupancy and release model to describe and analyze the entire operation process of mobile units (including shunting locomotives and small operation trains), so as to accurately evaluate the occupancy of each operating resource and optimize the line capacity configuration. By constructing a collaborative compilation model, the method realizes the synchronous scheduling of scheduled trains, shunting locomotives and small operation trains, and uses accurate simulation of the actual operating status of trains to improve the efficiency of railway transportation organization and management, providing important technical support for optimizing railway resource allocation and improving overall operating efficiency.

[0012] In order to achieve the above invention object, the technical solution adopted by the present invention is as follows:

[0013] A method for collaboratively compiling a train operation plan within a train operation section and a scheduled train plan comprises the following steps:

[0014] 1) Acquiring the operation data of the mobile unit and generating a speed-distance curve of the mobile unit, wherein the speed-distance curve reflects the continuous operation state of the mobile unit on each optional path, including acceleration, cruising, coasting, deceleration and braking;

[0015] 2) based on the speed-distance curve, calculating the occupation blocking time of each basic unit on each optional path of the mobile unit, thereby determining the blocking time of the mobile unit on each optional path;

[0016] 3) Input the block time and line information into a pre-established mixed integer model, which includes the following constraints:

[0017] a) Constraints on the mobile unit operation process to ensure that the mobile unit completes the continuous operation of starting, stopping, accelerating, cruising, coasting, decelerating and braking on the selected optional path;

[0018] b) Mobile unit path selection constraints, which stipulate that at the starting node and the end node, the mobile unit can only choose a unique optional path;

[0019] c) Occupancy conflict constraint for basic units. The big-M method is used to couple the entry and departure times of each basic unit to ensure that the same basic unit is occupied by only one moving unit at any given moment.

[0020] d) Power supply area capacity judgment constraint, which is used to count the number of moving units in the front and their operating energy consumption in the power supply area, and to judge whether the remaining power supply capacity of the current power supply area meets the requirements for subsequent moving units to enter.

[0021] 4) Use the rolling horizon algorithm to generate an initial feasible solution, and combine the adaptive large neighborhood search (ALNS) strategy and the simulated annealing acceptance strategy to solve the mixed integer model to obtain the final operation plan of shunting locomotives and local trains, so as to realize the collaborative compilation of the scheduled train plan and the train operation plan of the train operation section.

[0022] Furthermore, the speed–distance curve is obtained by simulating the acceleration, cruising, coasting, deceleration, and braking processes of the moving unit on each optional path through a simulation platform, or directly collected and generated by on-vehicle equipment of the moving unit operation control system.

[0023] Furthermore, the mixed integer model includes:

[0024] a) Constraints for the operation process of the moving unit, that is, it is required that the moving unit only has non-zero allowable times within each basic unit on its selected optional path, and the departure time between adjacent basic units is equal to the entry time of the next basic unit.

[0025] b) Moving unit path selection constraint to ensure that the moving unit flows out of only one optional path at the starting node and flows into only one optional path at the terminal node, and satisfies the inflow and outflow balance at each boundary node.

[0026] c) Occupancy conflict constraint for basic units. The big-M method is used to couple the entry and departure times of the moving unit in each basic unit.

[0027] Furthermore, the solution of the mixed integer model adopts a hybrid solution strategy composed of a rolling horizon algorithm, adaptive large neighborhood search (ALNS), and a simulated annealing acceptance strategy. The steps are as follows:

[0028] a) Use the rolling horizon algorithm to decompose the overall problem into several local sub-problems with finite time periods and generate an initial feasible solution.

[0029] b) Based on the initial solution, adopt the adaptive large neighborhood search strategy to locally disrupt and re-optimize some moving unit variables.

[0030] c) Combine the simulated annealing acceptance strategy to jump out of the local optimum and obtain a globally better solution.

[0031] Furthermore, the objective function of the mixed-integer model is as follows:

[0032]

[0033] where, represents the corresponding variable, and the goal is to minimize the total time occupied on the operation route of the mobile unit; represents the set of candidate paths of the mobile unit r at the terminal node , and the last basic unit of its candidate path is denoted as B l .

[0034] Furthermore, the mixed-integer model includes network flow balance constraints, and its mathematical expression is:

[0035]

[0036] where y t,l is a decision variable, and are the starting node and the terminal node of the mobile unit r respectively, is the set of demarcation points that the mobile unit r may pass through, and n is any node in the path.

[0037] Furthermore, the mixed-integer model uses the big M method to couple the entry and departure times of the basic units, specifically including the following constraints:

[0038]

[0039] where, represents the running time of the mobile unit r on the basic unit b of the optional path l, represents the residence time on the basic unit b; represents the set of basic units where the mobile unit r can stay on the candidate path l.

[0040] Furthermore, the mixed-integer model sets the following time window constraints on the departure time of the mobile unit at the starting station:

[0041]

[0042] where, and are the earliest and latest departure times of the mobile unit r respectively; represents the set of candidate paths of the mobile unit r at the starting node , and the first basic unit of its candidate path is denoted as

[0043] Further, the mixed-integer model includes a power supply area capacity judgment constraint. By counting the number of mobile units and the operating energy consumption in the power supply area, the following inequality is satisfied:

[0044]

[0045] Among them, R w represents the set of all mobile units in the power supply area w; W se represents the set of power supply areas within the interval; both r and r' are mobile units; r is the currently considered mobile unit, and r' is another mobile unit in the same power supply area; is a 0-1 variable used to indicate whether mobile unit r' enters the power supply area w earlier than mobile unit r. If so, it takes 1; otherwise, it is 0.; ω r,r′,w is a 0-1 variable used to indicate whether mobile unit r' leaves the power supply area w earlier than mobile unit r. If so, it takes 1; otherwise, it is 0; represents the energy consumption or the demand for power supply resources of mobile unit r' in the power supply area; χ w represents the total power supply capacity of the power supply area w; represents the energy consumption or the amount of power supply resources occupied by the current mobile unit r in the power supply area.

[0046] Further, the mixed-integer model includes a dynamic relationship constraint for maintenance tasks to determine the time dynamic relationship between mobile units and maintenance tasks. Some of its constraint expressions include:

[0047]

[0048] Among them, M represents a sufficiently large positive number (big M constant); represents a 0-1 variable indicating whether the departure time of mobile unit r in the influence area of maintenance task m is later than the start time of the maintenance task; P r represents the set of candidate paths of mobile unit r; P m represents the set of candidate paths related to maintenance task m; C p represents the set of track groups included in candidate path p. represents the set of track groups representing the end part in the influence area of maintenance task m; represents the departure time of mobile unit r on track group c of candidate path p; represents the start time of maintenance task m; MOT represents the set of maintenance tasks; R m represents the set of mobile units passing through the area of maintenance task m.

[0049] In another embodiment of the present invention, a collaborative compilation system for the train operation plan within the jurisdiction of the train operation section and the scheduled train plan is provided. This system can be used to implement the collaborative compilation method for the train operation plan within the jurisdiction of the train operation section and the scheduled train plan as described above. Specifically, it includes:

[0050] An operation data acquisition module, which is used to acquire the operation data of the mobile unit;

[0051] A speed - distance curve generation module, which generates the speed - distance curve of the mobile unit according to the acquired operation data;

[0052] A path analysis module, which analyzes the operation state of the mobile unit on different optional paths based on the speed - distance curve, and calculates the occupation block time of each basic unit to determine the block time of the mobile unit on each optional path;

[0053] A model construction module, which inputs the block time and line information into a pre - established mixed - integer model. The model includes constraints on the operation process of the mobile unit, constraints on the path of the mobile unit, and constraints on the occupation conflict of basic units;

[0054] A solution module, which is used to solve the mixed - integer model and generate the operation plans for shunting locomotives and local trains;

[0055] A display module, which is used to output and display the generated operation plans.

[0056] The present invention also discloses a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the collaborative compilation method for the train operation plan within the jurisdiction of the train operation section and the scheduled train plan as described above.

[0057] The present invention also discloses a computer - readable storage medium, on which a computer program is stored. When the program is executed by a processor, it implements the collaborative compilation method for the train operation plan within the jurisdiction of the train operation section and the scheduled train plan as described above.

[0058] Compared with the prior art, the advantages of the present invention are as follows:

[0059] 1. By organically integrating the scheduled train plan with the operations of shunting and local trains within the train operation section, synchronous scheduling of various operation plans is achieved, effectively improving the utilization rate of line and yard resources, shortening the waiting and scheduling time of trains, and overall improving the efficiency of railway transportation.

[0060] 2. By adopting the speed - distance curve of the mobile unit and the occupation and release model at the track level, the continuous operation states of the train such as acceleration, cruising, coasting, deceleration, and braking are finely described, making the model more in line with the actual working conditions, thereby improving the accuracy and practicability of the scheduling plan.

[0061] 3. By using the rolling horizon algorithm in combination with the adaptive large neighborhood search and simulated annealing acceptance strategy, the mixed-integer model is solved in real time and dynamically optimized, which can quickly respond to the changes in the on-site operation status, jump out of the local optimum, and obtain a high-quality operation plan.

[0062] 4. By using the big M method to couple the entry and departure times of basic units, the resource occupancy within the same section at the same moment is strictly controlled to ensure that there are no conflicts between mobile units, further ensuring the safe operation of train shunting and small operation trains.

[0063] 5. By dynamically judging and optimizing the power supply capacity configuration through real-time statistics of the number of mobile units and their operating energy consumption in the power supply area, the operation bottleneck problem caused by insufficient power supply resources is effectively avoided, and the utilization efficiency of power supply resources is improved. Brief Description of the Drawings

[0064] Figure 1 is the technical roadmap of the method for collaborative preparation of the train operation plan within the jurisdiction of the train operation depot and the scheduled train plan in the embodiment of the present invention;

[0065] Figure 2 is the schematic diagram of the operation path of the mobile unit in the embodiment of the present invention;

[0066] Figure 3 is the schematic diagram of the route conflict of the mobile unit in the embodiment of the present invention;

[0067] Figure 4 is the schematic diagram of the power supply area capacity limit of the mobile unit in the embodiment of the present invention. Detailed Embodiment

[0068] To make the purpose, technical solution and advantages of the present invention clearer and more understandable, the following further elaborates on the present invention in detail according to the drawings and by listing embodiments.

[0069] The present invention provides a method for collaborative preparation of the train operation plan within the jurisdiction of the train operation depot and the scheduled train plan. As Figure 1 shown, a mixed-integer model is established and solved according to the coupling relationship between the scheduled train, the locomotive running across stations, and the small operation trains to obtain the final operation plans of the locomotive running across stations and the small operation trains, so as to achieve efficient coordination of different transportation demands.

[0070] First, obtain the operation data of the mobile unit and generate its speed - distance curve. This curve can be obtained by simulating the acceleration, coasting, deceleration, and braking processes of the mobile unit on each optional path through a simulation platform, or directly reading relevant information from the on - vehicle equipment of the mobile unit operation control system. Based on this speed - distance curve, analyze the operation of the mobile unit on different optional paths, calculate the occupied block time of each basic unit, and thus determine the block time of the mobile unit on the optional path.

[0071] After obtaining the block time, input it together with the line information into the established mixed - integer model and solve the model. This model follows the operation rules of the mobile unit on the line and ensures safe operation by coordinating the conflicts of multiple mobile units within each basic unit. By adjusting the departure time, operation duration, and path of the mobile unit, make the solution satisfy the movement constraints, the mobile unit path constraints, and the occupancy limits of the basic units. Based on the optional path as the operation unit, achieve flexible adjustment of shunting locomotives and local trains, and at the same time ensure conflict - free operation with the scheduled trains, avoiding the waste of transport capacity caused by fixed interval time limits, thereby improving resource utilization efficiency.

[0072] Among them, the calculation of the mobile unit block time is based on the acceleration, coasting, deceleration, and braking processes on each optional path, specifically including:

[0073] 1. Road network construction

[0074] To more realistically present the road network information, a track - level road network is constructed in the research. This road network is composed of tracks and physical nodes between tracks connected to each other, and the core elements include tracks, track nodes, turnouts, signal machines, etc. The actual operation network of the mobile unit covers lines such as arrival and departure lines and shunting lines in railway stations. In the track - level road network, analyze the occupancy of the mobile unit on each basic unit, calculate and coordinate the occupancy conflicts between different mobile units to improve resource utilization efficiency.

[0075] 2. Mobile unit operation process

[0076] The running process of the mobile unit is combined with the basic units of the road network at the track level to achieve the occupation and release of the mobile unit at the track level; the occupation time of the mobile unit includes the turnout conversion time, the reserved time, the running time of the mobile unit, the buffer time, the clearing time of the mobile unit, and the line release time; among them, the route handling time refers to the time required for the turnout conversion when arranging the routes of the front and rear mobile units; the pre-occupation time refers to the time spent by the mobile unit traveling within the on-vehicle monitoring braking distance before entering the block section; the running time refers to the time from the head of the mobile unit entering the occupied block section to the head leaving the occupied block section; the clearing time is the time from the head of the mobile unit leaving the block section to the tail of the mobile unit leaving the block section; the release time refers to the block unlocking time after the mobile unit completely clears the occupied block section; when the block sections of different mobile units do not overlap in any basic unit, the running of the mobile unit does not conflict, thereby realizing the full utilization of railway resources.

[0077] 3. Mobile Unit Running Module

[0078] The complete running process of the mobile unit from start to stop is used as the basic control unit and is defined as an optional path. The optional path is composed of multiple track units connected in sequence, and its starting point and ending point correspond to the departure position and the termination position of the mobile unit's current running respectively. Since there are multiple shunting lines, there are multiple optional paths for the running operations from the locomotive depot to the shunting lines, from the shunting lines to the freight yard, etc. The mobile unit selects different optional paths during the running process to achieve non-conflicting running with the diagrammed trains, shunting locomotives, and local trains.

[0079] The speed-distance curve of the mobile unit is used to record the speed changes at any time and any mileage during its running process. This curve reflects the running conditions and states of the mobile unit within each track unit, including traction, cruise, coasting, and braking, and supports real-time speed acquisition, so as to ensure that the mixed integer model can accurately reflect the different running states of the mobile unit during calculation.

[0080] The running process of the mobile unit can be regarded as a complete journey along the optional path, including the start and stop stages, and is composed of stages such as traction, cruise, coasting, and braking. Its speed gradually increases from zero to the maximum running speed and then decelerates from the maximum speed to zero to ensure the speed coherence during the running process. In the road network, the selection of different optional paths determines the specific running state of the mobile unit, and this state is known. Therefore, by selecting a suitable optional path, the mobile unit can complete a complete driving process, which matches its speed curve, thereby improving the authenticity of the calculation results of the mixed integer model.

[0081] The mobile unit needs multiple start and stop processes to complete the complete operation task and needs to select different optional paths to jointly form the operation process of the mobile unit. Figure 3It can be seen that the complete operation process of the shunting locomotive from the locomotive depot to the arrival / departure yard can be composed of p2 and p6. At this time, the shunting locomotive transfers the goods to the freight yard through the shunting line 8; the shunting locomotive can also choose p4 and p5 to run from the locomotive depot to the freight yard, passing through the shunting line 7 at this time.

[0082] In addition, through a detailed analysis of the operation routes of mobile units within the station, it can be known that there may be route conflicts between the scheduled trains and the shunting locomotives or small transfer trains within the station. In Figure 4 the figure, the blue shaded part indicates the possible route conflicts between the scheduled trains and the shunting locomotives, while the red shaded part indicates the possible route conflicts between the scheduled trains. To effectively alleviate such conflicts, this study uses sub-paths to describe the operation processes of the shunting locomotives and small transfer trains, and through the selection of sub-paths by different operation units, the route conflicts within the station are resolved, thereby improving the overall coordination and operation efficiency of the mobile unit operation.

[0083] Furthermore, the integrated coupling mechanism of train operation management in the train operation depot and station dispatching:

[0084] The work carried out on the vehicles that need to handle cargo operations at intermediate stations within the section is called in-section work. It includes: cargo loading or unloading operations; sending cars to intermediate stations and taking out the loaded cars or empty cars after unloading from intermediate stations; shunting work at intermediate stations. The freight trains for sending cars to intermediate stations and taking cars from intermediate stations mainly include uncoupling and attaching trains, section small transfer trains, and dispatching locomotives, etc. The methods and times for taking and sending cars at intermediate stations, as well as the shunting methods at intermediate stations, are stipulated by compiling the in-section work plan diagram.

[0085] In the actual train operation plan, there may be track occupancy conflicts between the scheduled trains and the train operation plan within the train operation depot, which is very important for the coordinated compilation of the train operation plan within the train operation depot. Scheduled trains are trains stipulated in the officially compiled train operation diagram according to the railway transportation plan, serving passenger or freight transportation. The cross-station operation of locomotives refers to the locomotives performing transfer tasks between different stations without pulling trains, mainly for locomotive transfer, formation adjustment, or locomotive maintenance requirements. Small transfer trains are trains that perform repetitive, short-distance cargo transportation tasks within a specific area of the railway network (such as a station yard or a short-distance line). The operation characteristics and line occupancy situations of the three are shown in Table 1:

[0086] Table 1 Operation characteristics of scheduled trains, cross-station operation trains of locomotives, and small transfer trains

[0087]

[0088] As can be seen from the above table, the scheduled train has a clear origin station, destination station and passing stations, and its operation schedule, train number and speed level are fixed. And it has a higher priority to ensure the completion of passenger and freight transport services. The shunting locomotive, due to its high flexibility, can be adjusted according to real-time needs and the line idle situation. The local train mostly runs on the short-distance section or the shunting lines inside the station yard, which has repeatability and regularity, but is flexible in dispatching. It usually runs at fixed time intervals, but needs to occupy the station yard line resources for shunting operations. In the case of high-frequency operation, it exerts great pressure on the shunting locomotive operation and the throughput capacity of the station yard. All three occupy a certain degree of station yard resources and section resources, and their operation plans need to be considered collaboratively when being compiled.

[0089] The scheduled train, the shunting locomotive cross-station train and the local train each have their own characteristics in the compilation of the operation plan. The scheduled train is the core of railway transportation, and its operation plan needs to be compiled first, with a clear fixed schedule and line to ensure the maximization of the on-time rate and transportation capacity. When compiling the operation plan, it is necessary to accurately consider passenger and freight demands, the passing capacity of key nodes and the coordinated allocation of network-wide resources. The shunting locomotive cross-station train is characterized by flexibility, and its operation plan needs to be dynamically arranged around the gaps or low-density periods of the scheduled train to ensure the efficient execution of locomotive transfer or equipment dispatching tasks, while improving the line utilization rate. The operation plan of the local train needs to be combined with freight demands and station yard operation arrangements, based on the short-distance interval transportation with strong regularity, to ensure the timely transfer of freight car bodies between station yards, and at the same time reasonably avoid the scheduled train and shunting locomotive tasks to avoid resource conflicts. The compilation of the operation plans of these three types of mobile units needs to make full use of railway network resources, and through scientific dispatching and dynamic optimization, achieve the efficient coordination of different transportation demands, improve the overall transportation efficiency and network operation stability. Therefore, in this study, when collaboratively compiling the three, the operation plan of the scheduled train is first compiled according to the train operation plan, and then the shunting locomotive operation and the local train are drawn on this basis.

[0090] Furthermore, a mixed integer model for collaborative compilation of the train operation plan within the jurisdiction of the train operation section and dynamic allocation of the route resources is established:

[0091] 1. Operation process of the mobile unit

[0092] The mobile unit needs to select the best route from the optional routes, and only the basic units on the selected route have non-zero allowed times, while the times of the basic units on the unselected routes are zero. Its operation time is fixed, including the time for pre-occupying, entering, leaving, emptying and releasing the basic units. The departure time of the origin basic unit is limited by a specific time window. Within the same route, the time when the mobile unit leaves the previous basic unit should be consistent with the time when it enters the next basic unit. For the mobile unit that needs to stop at stations, its dwell time on the line basic unit should be within a certain range and can be adjusted according to operation requirements.

[0093] 2. Path Constraints of Mobile Units

[0094] For all selected paths of the mobile unit, ensure that the outgoing optional path of the mobile unit at the departure node is unique, the incoming optional path at the terminal station is unique, and ensure that the number of incoming and outgoing optional paths of the mobile unit at each demarcation point is the same.

[0095] 3. Occupancy Rules of Basic Units

[0096] The set of stations Z forms the railway operation line. According to the construction rules of the track-level road network, the station z ∈ Z is composed of basic units b ∈ B, and n ∈ N are the two end nodes of the track. R is the set of mobile units. L is the set of optional paths, and each optional path l ∈ L is composed of basic units b ∈ B connected end to end r Composed of Is the first basic unit of the optional path l b l Represents the last basic unit of the optional path l And Respectively represent the starting node and the terminal node of the mobile unit r. L r Is the set of optional paths that the mobile unit r may pass through Represents the set of demarcation points of the optional paths that the mobile unit r may pass through And Are respectively the sets of optional paths that flow out of and into the node n and that the optional path r may pass through. B l Is the set of basic units included in the optional path l Is the set of basic units where the mobile unit r can stay on the optional path l Represents the running time of the mobile unit r passing through the basic unit b on the optional path l Represents the staying time of the mobile unit r at the basic unit b of the optional path l. In this model, the mobile unit refers to the shunting locomotive and the local train mobile unit

[0097] Table 2 Variable Table

[0098]

[0099]

[0100] Objective Function: The model is based on the train operation diagram of the scheduled trains with higher priority. Since the train schedule of the scheduled trains has been determined, in order to lay out as many local trains and shunting trains across stations as possible on the basis of the train operation diagram of the scheduled trains, the objective function of the model is to minimize the time occupied by the operation line of the mobile unit on the train operation diagram

[0101]

[0102]

[0103] Formula (2) is the network flow balance constraint, which is to ensure that the optional path for small operation trains and shunting trains to flow out of the departure station is unique, the optional path for flow into the terminal station is unique, and the number of optional paths for the mobile unit to flow in and out of each demarcation point is the same; there are multiple optional path sets for small operation trains and shunting trains from the departure station to the terminal station. Through the optional path selection of the mobile unit, the arrival and departure line usage plan of the mobile unit is determined, so that the conflicts between small operation trains, shunting trains and scheduled trains are relieved, and the quality of the operation diagram is improved.

[0104]

[0105] The Big M method is used to couple the occupation of the optional path by the small operation train and the shunting train across the station with the entry time and departure time of each basic unit of the optional path by the small operation train and the shunting train across the station. Through the time coupling, it is ensured that there will be no conflict between the small operation train, the shunting train across the station and the scheduled train. If the mobile unit r will not occupy each basic unit via the optional path l, the time when the mobile unit r enters each basic unit and leaves each basic unit via the optional path l is 0.

[0106] When a small-scale running train and a shunting train arrive at a station and stop at the station's arrival and departure line, the running time and residence time of the mobile unit on the basic unit need to be considered separately. The running time of the mobile unit r on the basic unit b is obtained by combining the mobile unit speed curve with the running mileage to obtain the running time of mobile units of different speed levels on the basic unit. As the input data of the model, the running process of the mobile unit is consistent with the actual speed curve on site.

[0107] The departure time of small-scale trains and shunting trains at their departure stations is required to be within the given time window. It ensures the coordination of the operating times of each mobile unit, improves the utilization of transportation capacity, and meets the needs of passengers and cargo owners.

[0108]

[0109] In the formula represents the destination node of mobile unit r, They represent the previous basic unit and the next basic unit corresponding to the node n included in the optional path l. In order to maintain the consistency of the operation process of the mobile unit on the road network with large granularity, it is necessary to connect the entry and exit time of each basic unit. If two consecutive basic units are occupied by the same mobile unit, the time when the mobile unit head leaves the previous basic unit is equal to the time when it enters the next basic unit. Equations (9) and (10) consider two consecutive basic units belonging to different optional paths and the same path respectively.

[0110]

[0111] The actual dwell time of local passenger trains and shunting locomotives across stations on arrival and departure tracks is greater than their minimum dwell time and cannot exceed the predetermined maximum dwell time to ensure sufficient time for operations.

[0112]

[0113] Equations (13) and (14) constrain the occupancy time of the alternative paths in the basic unit to describe the actual occupancy of the basic unit by local passenger trains and shunting locomotives across stations.

[0114]

[0115]

[0116] Equations (15) and (16) handle the conflict problem between two moving units on the same basic unit. To ensure the safe operation between moving units, local passenger trains or shunting locomotives across stations do not conflict with the scheduled trains. When local passenger trains and shunting locomotives across stations are running on the line, they need to maintain the uniqueness of the spatio-temporal occupancy of the line resources. Only one moving unit can occupy a basic unit at any moment, and the occupancy times of different moving units on the same basic unit cannot overlap. When two moving units pass through the same basic unit successively, it may involve different route arrangement times

[0117] According to the 0-1 relational variables used, the number of moving units in the power supply section in a certain state can be judged. According to the difference between the power supply capacity of the power supply section and the total operating energy consumption of the moving units in the current power supply section, it can be judged whether the next moving unit is allowed to enter the power supply section. For example Figure 4 , for the power supply section w∈W in the interval se , count the number of moving units that entered the power supply section earlier than the current moving unit and the number of moving units that left the power supply section earlier, and judge the difference between the power supply capacity and the operating energy consumption of the moving units. When the subtraction of the two is less than or equal to the operating energy consumption of the current moving unit, the current moving unit can enter the power supply section. For the power supply section w∈W that contains a station st , in addition to counting the number of moving units that entered and left the power supply section earlier than the current moving unit, it is also necessary to consider the number of moving units that entered and left the station earlier than the current moving unit to eliminate the influence of the moving units parked in the station, so as to calculate the remaining capacity in the current power supply section. The above situation also needs to be considered when the moving unit parked in the arrival and departure tracks of the station is about to leave the station.

[0118] Power supply section in the interval:

[0119] Equations (17) and (18) are used to calculate the time when each mobile unit enters and leaves the power supply section. According to the mobile unit r passing through the sub-path, the first track group when entering and leaving the power supply section w where it is located and the last track group to calculate.

[0120]

[0121] Using and ω r,r′,w respectively mark the number of mobile units that entered the power supply section earlier than this moment and the number of mobile units that left the power supply section earlier than this moment at a certain moment. Equations (19) and (20) count the number of mobile units that entered the power supply section earlier than the current mobile unit; Equations (21) and (22) count the number of mobile units that left the power supply section earlier than the current mobile unit; in Equation (23) and Subtracting them gives the energy consumption required by the mobile units in the current power supply section when the mobile unit r enters the power supply section, and determines whether the remaining power supply capacity of the current power supply section can meet the requirements of the mobile unit r.

[0122]

[0123] Mobile unit enters the cross-station power supply section from the interval:

[0124] For the cross-station power supply section w ∈ W st , it is also necessary to count the number of mobile units in the power supply section. In addition to counting the number of mobile units at the entrance and exit of the power supply section, the mobile units parked on the arrival and departure lines in the station also need to be considered. Subtracting the mobile units parked on the arrival and departure lines in the power supply section, so when counting the number of mobile units in the current power supply section, the number of mobile units parked on the arrival and departure lines in the current power supply section needs to be subtracted. Equations (24) and (25) calculate the time when each mobile unit r enters and leaves the cross-station power supply section.

[0125]

[0126] Equations (26) and (27) represent the time when each mobile unit enters and leaves the station s in the power supply section w ∈ Wst. The moment when the mobile unit enters the station is the time when the mobile unit leaves the current power supply section, and the moment when it leaves the station is the time when the mobile unit re-enters the power supply section.

[0127]

[0128] Equations (28), (29), (30), and (31) count the number of mobile units that entered and left the power supply subzone entrance / exit earlier than the current mobile unit.

[0129]

[0130] Equations (32), (33), (34), and (35) count the number of mobile units that entered the station earlier than the current mobile unit and the number of mobile units that left the station earlier than the current mobile unit. When mobile unit r' stops at the station, the value is 1.

[0131]

[0132] It should be noted that there is a possibility of dynamically adjusting the stop plan for the mobile unit. When mobile unit r' does not stop at station s, there is no need to judge the possible order relationship between mobile units r and r' at the station, and the variables δ r,r′,w and ∈ r,r′,w should be 0 at this time. When mobile unit r' stops at the station, the variables δ r,r′,w and ∈ r,r′,w may be 1 or 0.

[0133] Therefore, equations (36) and (37) are used for limited constraints.

[0134]

[0135]

[0136] Equation (38) counts the above four 0-1 variables and judges the remaining power supply capacity in the power supply subzone at the current moment. If the constraint (38) is satisfied, it means that mobile unit r can enter this power supply subzone.

[0137]

[0138] The situation of entering the cross-station power supply subzone from the station:

[0139] For a mobile unit located on the arrival / departure line of the station, after it meets the departure condition and leaves the arrival / departure line, it needs to re-occupy the power supply subzone resources, and it is necessary to judge the power supply capacity of the current power supply subzone. Equations (39), (40), (41), and (42) count the number of mobile units that entered and left this power supply subzone earlier than the current mobile unit.

[0140]

[0141] Equations (43), (44), (45), and (46) count the number of mobile units that entered the arrival / departure line of the power supply subzone station earlier than the current mobile unit r and the number of mobile units that left the arrival / departure line of the power supply subzone station earlier than the current mobile unit r.

[0142]

[0143]

[0144] Equations (47), (48), (49) and (50) impose constraints on 0-1 variables. When the mobile unit r or r′ does not stop at the station s, the values of κ r,r′,w and ρ r,r′,w should be 0.

[0145]

[0146] Equation (51) determines the remaining power supply capacity of the power supply section at the current moment. If the constraint (51) is satisfied, it means that the mobile unit r can enter the power supply section from the station at this moment.

[0147]

[0148] Maintenance time constraint:

[0149] Dynamic relationship constraint between the operation and maintenance tasks of the mobile unit: Constraints (53) to (54) are used to determine the dynamic relationship between the occupancy time of the mobile unit in the section where the maintenance task m is located and the start and end times of the maintenance task. This dynamic relationship, combined with constraints (55) and (56), jointly determines the optional sub-paths of the mobile unit. To more clearly depict this relationship, these constraints first need to introduce some important set concepts, including R m , Maintenance task m1 is being carried out on the downlink line (23, 31) of the section. First, all mobile units passing through this section are classified. Among them, the uplink mobile units all belong to the set of mobile units moving in the opposite direction to the direction of the line where the maintenance plan is located The downlink mobile units belong to the set of mobile units moving in the same direction as the direction of the line where the maintenance plan is located, R m1 . Then, all the tracks affected by the maintenance in the section are classified. Driving along the line direction of the maintenance task m1 (i.e., the downlink direction), considering that both lines can organize two-way operation, the tracks that the mobile unit may pass through first in the section are (23, 25) or (24, 26), and the tracks that it may pass through last are (29, 31) or (30, 32). It is defined that the tracks (23, 25) and (24, 26) form the set while the tracks (29, 31) and (30, 32) form the set

[0150] Constraints (53) to (56) construct the dynamic relationship between the time when the mobile unit ends occupying the maintenance section and the start time of the maintenance task. For any mobile unit r ∈ R moving in the same direction as the line where the maintenance task m is located m, the time to end occupying the maintenance section can be replaced by the cumulative sum of the time of the last track that the mobile unit may pass through within the section it occupies. When When takes the value of 1, constraint (53) stipulates that the time for mobile unit r to end occupying the maintenance section should be greater than or equal to the start time of maintenance m. On the contrary, when takes the value of 0, constraint (54) stipulates that the time for the mobile unit to end occupying the maintenance section should be less than or equal to the start time of maintenance m. Similarly, for any mobile unit in the opposite direction of the line where the maintenance task m is located Constraints (55) and (56) stipulate the corresponding size relationships between the time for the mobile unit to end occupying the section and the start time of the maintenance task under different values.

[0151]

[0152] Constraints (57) to (60) construct the dynamic relationship between the time for the mobile unit to start occupying the maintenance section and the end time of the maintenance task. For any mobile unit r ∈ R in the same direction as the line where the maintenance task m is located m , its start occupying time can be replaced by the cumulative sum of the time of the first track that the mobile unit may pass through within the section it starts to occupy When takes the value of 1, constraint (57) stipulates that the end time of maintenance task m is greater than or equal to the time for mobile unit r to start occupying the maintenance section. On the contrary, when takes the value of 0, constraint (58) stipulates that the end time of maintenance task m is less than or equal to the time for mobile unit r to start occupying the maintenance section. Similarly, for any mobile unit in the opposite direction of the line where the maintenance task m is located Constraints (59) and (60) stipulate the corresponding size relationships between the time for the mobile unit to start occupying the section and the end time of the maintenance task under different values.

[0153]

[0154] Furthermore, the dynamic relationship between the operation of the mobile unit and the maintenance task can be represented by and . When and both equal 1, the occupancy time of mobile unit r in the section intersects with the maintenance task time, indicating that the mobile unit is affected by the maintenance task, and its running speed and sub-path selection will be different from the normal situation. Constraints (61) and (62) introduce the 0-1 variable β r,m to represent and Relationship. According to the constraints, if and both equal 1, then β r,m will also be assigned the value 1. On the contrary, when and are not both 1, β r,m will be assigned the value 0.

[0155]

[0156] Sub - path judgment constraints for the mobile unit: Constraints (63) and (64) constrain the sub - path selection of the mobile unit under the influence of maintenance. In constraint (63), for any mobile unit r ∈ R in the same direction as the line where the maintenance is located m , when β r,m takes the value 1, that is, when the mobile unit r is affected by the maintenance task m, the mobile unit can select a sub - path in the interval in the opposite direction of the running direction of the mobile unit On the contrary, when β r,m takes the value 0, the mobile unit is not affected by the maintenance task and cannot select a sub - path in the opposite direction of the original running direction, and the corresponding x r,p is forced to be assigned the value 0. In constraint (64), when β r,m takes the value 1, at this time the maintenance is in progress, and any mobile unit r cannot select a sub - path passing through the line where the maintenance task is located and its corresponding x r,p is forced to be assigned the value 0. When β r,m takes the value 0, the mobile unit is not affected by the maintenance, the value of x r,p is not restricted, and the mobile unit can pass through the sub - path of the line where the maintenance task is located.

[0157]

[0158] Mobile unit speed limit constraint: Constraint (65) limits the running speed of the mobile unit in the maintenance interval during the maintenance task. For any mobile unit r, when β r,m and x r,p are both 1, the running time of the mobile unit on all tracks c ∈ C p ∩C m in the maintenance interval via path p needs to be extended by w times to achieve speed limit.

[0159]

[0160] Furthermore, the mixed - integer model solution algorithm:

[0161] The rolling horizon algorithm coupled with the large neighborhood search algorithm innovatively introduces the large neighborhood search algorithm into the solution of the proposed model. This algorithm uses the rolling horizon algorithm to obtain an initial feasible solution and then adopts the large neighborhood search algorithm to improve the solution.

[0162] The rolling horizon algorithm is an online optimization algorithm based on real-time data and is widely used in the problem of the operation diagram of mobile units. After adopting this algorithm, the model can adjust the result of the current solution in real time according to the data solved in the previous stage, and comprehensively utilize historical data and model information for optimization, with strong robustness. The rolling horizon algorithm decomposes the problem of compiling the operation diagram of mobile units in the time domain into a series of continuously rolling small-scale sub-problems or local problems with limited time periods to replace a large-scale or infinite-time global problem. The solution of each sub-problem only uses part of the information known at the current moment. At each decision moment, using the current known information, a rolling window is determined, and according to a certain rolling rule, it is decided which information to consider in this local sub-problem, and then the local operation diagram sub-problem of the mobile unit is solved within this window. The completion moment of this part of the solution is the new scheduling moment, and the solution result will also be used as the known local information at the next decision moment. This process is repeated iteratively until all sub-problems are solved.

[0163] The large neighborhood search algorithm (LNS) is a heuristic algorithm that starts from an initial solution and destroys a part of the current solution in each iteration, and obtains an improved overall solution after re-optimization. The key point of the large neighborhood search algorithm is to select fixed variables to create a partial solution, and the number of fixed variables affects the size of the neighborhood. The algorithm proposed in this study is an improved adaptive large neighborhood search (ALNS). This algorithm obtains an initial feasible solution through the rolling horizon algorithm. After that, the algorithm designs a variety of neighborhood search strategies, including random selection, neighborhood search strategies based on the maximum total travel time and based on the maximum stop time at intersections. Fix the variables of all mobile units except the selected mobile units and re-solve the selected part of the mobile units. The probabilities of these strategies being selected are continuously updated in a dynamic learning process. When each strategy is selected, based on whether it improves the current solution, the weights of the strategies are dynamically adjusted through the roulette algorithm. According to the change of the weights, the probabilities of each strategy being selected are changed, enhancing the diversity and efficiency in the search process. The algorithm adopts a simulated annealing acceptance strategy to avoid falling into local optima and ensure that the iteration of the algorithm moves in the direction of making the feasible solution better, so as to obtain a high-quality feasible solution.

[0164] In another embodiment of the present invention, a collaborative compilation system for the train operation plan within the jurisdiction of the train operation depot and the scheduled train plan is provided. This system can be used to implement the collaborative compilation method for the train operation plan within the jurisdiction of the train operation depot and the scheduled train plan. Specifically, it includes:

[0165] An operation data acquisition module, configured to acquire the operation data of the mobile unit;

[0166] A speed–distance curve generation module, configured to generate a speed–distance curve of the mobile unit according to the acquired operation data;

[0167] A path analysis module, configured to analyze the operation state of the mobile unit on different alternative paths based on the speed–distance curve, and calculate the occupation blocking time of each basic unit to determine the blocking time of the mobile unit on each alternative path;

[0168] A model construction module, configured to input the blocking time and line information into a pre-established mixed integer model, where the model includes constraints on the operation process of the mobile unit, constraints on the path of the mobile unit, and constraints on the occupation conflict of basic units;

[0169] A solving module, configured to solve the mixed integer model and generate an operation plan for the shunting locomotive and local train;

[0170] A display module, configured to output and display the generated operation plan.

[0171] In another embodiment of the present invention, a terminal device is provided. The terminal device includes a processor and a memory. The memory is used to store a computer program. The computer program includes program instructions. The processor is used to execute the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is adapted to implement one or more instructions, specifically adapted to load and execute one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention may be used for the operation of the method for jointly formulating the train operation plan within the jurisdiction of the train operation section and the scheduled train plan.

[0172] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a terminal device and is used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and, of course, the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, and the operating system of the terminal is stored in this storage space. Moreover, one or more instructions suitable for being loaded and executed by a processor are stored in this storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory.

[0173] One or more instructions stored in the computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the method for coordinating the compilation of the train operation plan within the jurisdiction of the train operation section and the scheduled train plan in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by a processor.

[0174] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0175] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0176] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes and / or blocks Figure 1 in one or more of the processes and / or blocks Figure 1 specified in the block or blocks.

[0177] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes and / or blocks Figure 1 in one or more of the processes and / or blocks Figure 1 specified in the block or blocks.

[0178] Those of ordinary skill in the art will recognize that the embodiments described herein are for the purpose of assisting the reader in understanding the implementation of the present invention and should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. Those of ordinary skill in the art can make various other specific deformations and combinations without departing from the essence of the present invention based on the technical revelations disclosed in the present invention, and these deformations and combinations are still within the scope of protection of the present invention.

Claims

1. A method for collaborative compilation of train operation plans within the jurisdiction of a train operation section and the scheduled train plans, characterized in that: It includes the following steps: 1) Obtain the operation data of the mobile unit and generate a speed - distance curve of the mobile unit, where the speed - distance curve reflects the continuous operation states of the mobile unit accelerating, cruising, coasting, decelerating, and braking on each optional path; 2) Based on the speed - distance curve, calculate the occupancy block time of each basic unit of the mobile unit on each optional path, so as to determine the block time of the mobile unit on each optional path; 3) Input the block time and line information into a pre - established mixed - integer model, and the mixed - integer model includes the following constraints: a) Mobile unit operation process constraint, ensuring that the mobile unit completes continuous operations of starting, stopping, accelerating, cruising, coasting, decelerating, and braking on the selected optional path; b) Mobile unit path selection constraint, stipulating that at the starting node and the terminal node, the mobile unit can only select a unique optional path; c) Basic unit occupancy conflict constraint, using the big - M method to couple the entry and departure times of each basic unit, ensuring that the same basic unit is occupied by only one mobile unit at any moment; d) Power supply area capacity judgment constraint, used to count the number of leading mobile units in the power supply area and their operation energy consumption, and judge whether the remaining power supply capacity of the current power supply area meets the entry requirements of subsequent mobile units; 4) Use the rolling - horizon algorithm to generate an initial feasible solution, and combine the adaptive large - scale neighborhood search strategy and the simulated annealing acceptance strategy to solve the mixed - integer model, and obtain the final operation plan of the shunting locomotive and local trains, so as to realize the collaborative compilation of the diagrammed train plan and the train operation plan of the train operation section.

2. A collaborative compilation method for train operation plans within the jurisdiction of a train operation section and the scheduled train plans according to claim 1, characterized in that: The mixed - integer model includes: a) Mobile unit operation process constraint, that is, it is required that the mobile unit only has non - zero allowed moments within each basic unit on its selected optional path, and the departure time between adjacent basic units is equal to the entry time of the next basic unit; b) Mobility unit path selection constraints to ensure that at the starting node of the mobility unit only one alternative path flows out, and at the terminating node only one alternative path flows in, and the inflow and outflow are balanced at each boundary node; c) Basic unit occupancy conflict constraint, using the big - M method to couple the entry and departure times of the mobile unit in each basic unit.

3. A collaborative compilation method for train operation plans within the jurisdiction of a train operation depot and the scheduled train plans as described in claim 1, characterized in that: The solution of the mixed - integer model adopts a hybrid solution strategy composed of the rolling - horizon algorithm, the adaptive large - scale neighborhood search, and the simulated annealing acceptance strategy, and its steps are as follows: a) Use the rolling - horizon algorithm to decompose the overall problem into several local sub - problems of finite time periods and generate an initial feasible solution; b) On the basis of the initial solution, adopt the adaptive large - scale neighborhood search strategy to locally disrupt and re - optimize some mobile unit variables; c) Combine the simulated annealing acceptance strategy to jump out of the local optimum and obtain a globally better solution.

4. A collaborative compilation method for train operation plans within the jurisdiction of a train operation section and the scheduled train plans as described in claim 1, characterized in that: The objective function of the mixed - integer model is as follows: Among them, represents the corresponding variable, and the goal is to minimize the total time occupied on the running route of the mobile unit; represents the set of candidate paths of the mobile unit r at the end node The last basic unit of its candidate path is denoted as B l .

5. A method for collaborative compilation of train operation plans within the jurisdiction of a train operation section and the scheduled train plans as described in claim 1, characterized in that: The mixed - integer model includes network flow balance constraints, and its mathematical expression is: Among them, y r，l is a decision variable, and are the starting node and the ending node of mobile unit r respectively, is the set of demarcation points that mobile unit r may pass through, and n is any node in the path.

6. A method for collaborative compilation of train operation plans within the jurisdiction of a train operation section and the scheduled train plans according to claim 1, characterized in that: The mixed - integer model uses the big - M method to couple the entry and departure times of basic units, specifically including the following constraints: Among them, represents the running time of the mobile unit r on the basic unit b of the optional path l, represents the residence time on the basic unit b; represents the set of basic units where the mobile unit r can stay on the candidate path l.

7. A method for collaborative compilation of train operation plans within the jurisdiction of a train operation section and the scheduled train plans as described in claim 1, characterized in that: The mixed - integer model sets the following time - window constraints on the departure time of the mobile unit at the starting station: Among them, and are the earliest and latest departure times of the mobile unit r, respectively; represents the set of candidate paths of the mobile unit r at the starting node The first basic unit of its candidate path is denoted as 8. A collaborative compilation method for train operation plans within the jurisdiction of a train operation section and the scheduled train plans as described in claim 1, characterized in that: The mixed - integer model includes power supply area capacity judgment constraints. By counting the number of mobile units and their operation energy consumption in the power supply area, the following inequality is satisfied: Among them, R w represents the set of all mobile units within the power supply zone w; W se represents the set of power supply zones within the interval; r and r′ are both mobile units; r is the currently considered mobile unit, and r′ is another mobile unit within the same power supply zone; is a 0-1 variable used to indicate whether mobile unit r′ enters the power supply zone w earlier than mobile unit r. If so, it takes 1; otherwise, it is 0.; ω r，r′，w is a 0-1 variable used to indicate whether mobile unit r′ leaves the power supply zone w earlier than mobile unit r. If so, it takes 1; otherwise, it is 0; represents the energy consumption or the demand for power supply resources of mobile unit r′ in the power supply zone; χ w represents the total power supply capacity of the power supply zone w; represents the energy consumption or the amount of power supply resources occupied by the current mobile unit r in the power supply zone.

9. A method for collaborative compilation of train operation plans within the jurisdiction of a train operation section and the scheduled train plans as described in claim 1, characterized in that: The mixed-integer model includes constraints on the dynamic relationship of maintenance tasks to determine the time dynamic relationship between mobile units and maintenance tasks. Some of the constraint expressions are as follows: Where M represents a sufficiently large positive number; is a 0-1 variable indicating whether the departure time of mobile unit r within the influence area of maintenance task m is later than the start time of the maintenance task; P r represents the set of candidate paths of mobile unit r; P m represents the set of candidate paths related to maintenance task m; C p represents the set of track groups included in candidate path p; represents the set of track groups indicating the end part in the influence area of maintenance task m; represents the departure time of mobile unit r from track group c on candidate path p; represents the start time of maintenance task m; MOT represents the set of maintenance tasks; R m represents the set of mobile units passing through the area of maintenance task m.

10. A collaborative compilation system for train operation plans within the jurisdiction of a train operation depot and the scheduled train plans, characterized in that: This system can be used to implement the collaborative compilation method of the train operation plan within the jurisdiction of the train operation section and the scheduled train plan described in any one of claims 1 to 9. Specifically, it includes: An operation data acquisition module for acquiring the operation data of mobile units; A speed–distance curve generation module for generating the speed–distance curve of mobile units based on the acquired operation data; A path analysis module for analyzing the operation states of mobile units on different alternative paths based on the speed–distance curve and calculating the occupied block times of each basic unit to determine the block times of mobile units on each alternative path; A model construction module for inputting the block times and line information into a pre-established mixed-integer model, which includes constraints on the operation process of mobile units, constraints on the paths of mobile units, and constraints on occupancy conflicts of basic units; A solution module for solving the mixed-integer model and generating the operation plans of shunting locomotives and local trains; A display module for outputting and displaying the generated operation plans.

Images