Method and product for coordinated allocation of train resources and warehouses in rail traffic dispatching

Abstract

The application provides a method and product for train resource and warehouse coordination configuration in rail transit scheduling, breaks through the existing scheduling mode mainly based on fixed operation diagram or simple train level planning, and cooperatively realizes response of station passenger flow demand, train turnaround transportation and warehouse capacity control, generates a potential train set adapted to the space-time characteristics of station passenger flow by taking station passenger flow as a driving force, and cooperatively verifies the occupation, recovery and warehouse operation of train resource through train connection relationship variable, so that the obtained scheduling result not only meets the passenger flow demand at the train level, but also has engineering executability at the train and warehouse level, fundamentally avoids the problem of mutual fragmentation between train operation plan and train resource configuration and warehouse capacity, and the obtained train operation plan and train scheduling plan have engineering implementability.

Description

Technical Field

[0001] This application relates to the field of urban rail transit technology, specifically to a method and computer program product for the coordinated allocation of train resources and warehouses in rail transit scheduling. Background Technology

[0002] With the continuous expansion of urban rail transit networks and the increasing complexity of operations between lines and sections, train operation scheduling has evolved from a simple organization mode of single lines and fixed formations to a complex system engineering project involving multiple lines, multiple turnaround points, and multiple depots. In existing rail transit scheduling methods, train operation organization is usually centered on a predetermined timetable, and the train operation plan and the use of train resources and depots are often planned and implemented separately in stages.

[0003] In actual operation, passenger flow at stations exhibits significant imbalances in both time and space, with substantial differences in train capacity demand across different time periods and stations. The established timetable is disconnected from station passenger flow, making it impossible to generate train schedules that match station passenger demand. Furthermore, there is a lack of coordinated control over train resource utilization, turnaround connections, and depot capacity. This has become a significant technical bottleneck restricting the engineering feasibility of rail transit scheduling. Summary of the Invention

[0004] One objective of this application is to address the technical problem of how to respond to station passenger flow and avoid a disconnect between the resulting train schedule and the utilization, recycling, and storage capacity of train resources.

[0005] According to one aspect of the embodiments of this application, a method for the coordinated allocation of train resources and warehouses in rail transit scheduling is disclosed, the method comprising:

[0006] Adapting to the spatiotemporal distribution of passenger flow at stations, a potential train set for the target city's rail transit to meet passenger flow demand is generated. The potential trains in the potential train set are identified by their starting station and train number.

[0007] In the set of potential train services, enumerate and filter the previous and next potential train services that have the possibility of being connected in terms of time and space, and the previous and next potential train services form a train service pair.

[0008] For the train number pair, a connection relationship variable between the preceding and following train numbers is constructed. The connection relationship variable between the preceding and following train numbers is used to indicate that the same train is turned back from the previous potential train number to carry the next potential train number.

[0009] Based on the variables of the connection relationship between the preceding and following trains, a collaborative constraint verification is performed on the train resource occupation, recycling, and warehouse management of the potential train set.

[0010] For the set of potential train numbers that meet the constraints and the corresponding train control variables, generate a train operation plan and a train scheduling plan adapted to warehouse capacity under the train operation plan.

[0011] According to one aspect of the embodiments of this application, a computer device is disclosed, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method as described in any of the preceding claims.

[0012] According to one aspect of the embodiments of this application, a computer program product is disclosed, including a computer program that, when executed by a processor, implements the steps of the method as described in any of the preceding claims.

[0013] According to one aspect of the embodiments of this application, a computer-readable storage medium is disclosed having a computer program stored thereon that, when executed by a processor, implements the steps of the method as described in any of the preceding claims.

[0014] This application's embodiments break through the existing scheduling models that primarily rely on fixed timetables or simple train number-level planning. It collaboratively achieves response to station passenger flow demands, train turnaround operations, and warehouse capacity management. Driven by station passenger flow, it generates a set of potential train numbers adapted to the spatiotemporal characteristics of station passenger flow. Then, based on this, it explicitly describes the variables relating to preceding and following train numbers, and accordingly verifies the collaborative constraints on train resource occupation, recovery, and warehouse operations. This ensures that the resulting scheduling not only meets passenger flow demands at the train number level but also possesses engineering feasibility at the train and warehouse levels. It fundamentally avoids the problem of separation between train number operation plans, train resource allocation, and warehouse capacity. Consequently, the resulting train number operation plans and train scheduling plans possess engineering feasibility, avoiding the separation between train number operation plans and train resource allocation, i.e., avoiding the defect of separation between the resulting train number operation plans and the occupation, recovery, and warehouse capacity of train resources.

[0015] Specifically, the embodiments of this application first use the spatiotemporal distribution of passenger flow at the station as the direct input of scheduling requirements. By mapping the passenger flow demand at the station in different driving directions and waiting time slices to the train carrying demand, a potential set of trains for carrying passenger flow is generated, ensuring from the source that the resulting train operation plan can have the ability to respond to actual changes in passenger flow.

[0016] Building upon this foundation, instead of controlling the trains carried by each potential train in isolation, the system enumerates and filters potential train pairs within the set of potential trains, selecting those with temporal and spatial continuity. This identifies possible routes for trains to continuously operate between different train pairs. A variable representing the connection between preceding and following train pairs is introduced to clarify whether the same train is rerouted from a preceding potential train to carry a subsequent potential train, providing an explicit modeling basis for the continuous utilization of train resources at the train level.

[0017] Furthermore, based on the constructed variables relating to preceding and following train services, the occupation and recovery of train resources and the management of warehouse entry and exit are integrated into the constraint verification process. The destination of trains between services, warehouse availability, and the uniqueness of resource usage are verified collaboratively. Thus, while generating the train service plan, the feasibility of train resources and warehouse capacity is simultaneously verified to obtain the corresponding train scheduling plan. This achieves the integrated output of the train service plan and the train resource allocation scheme, i.e., the train scheduling plan.

[0018] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0019] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this application. Attached Figure Description

[0020] The above and other objectives, features and advantages of this application will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0021] Figure 1 A flowchart illustrating a method for the coordinated allocation of train resources and warehouses in rail transit scheduling according to an embodiment of this application is shown.

[0022] Figure 2 It is based on Figure 1 The flowchart described in the corresponding embodiment describes the steps of generating a set of potential train services to meet the passenger flow demand of the target city's rail transit system by adapting the spatiotemporal characteristics of passenger flow at the station.

[0023] Figure 3 It is based on Figure 2 The corresponding embodiment shows a flowchart describing the steps of determining the set of potential train services that can carry station passenger flow based on the station passenger flow matching variables corresponding to each station in each waiting time slot and direction of travel.

[0024] Figure 4This is a flowchart illustrating a method for constructing train departure variables and train interval variables for controlling operating intervals from a set of potential trains, according to an exemplary embodiment.

[0025] Figure 5 It is based on Figure 1 Corresponding implementation in Figure 4 The flowchart describes the method for verifying the collaborative constraints of train resource occupation, recovery, and warehouse management of potential train sets based on the train number operation variables and train number interval variables constructed in the corresponding embodiment and the variables of the connection relationship between preceding and subsequent train numbers.

[0026] Figure 6 It is based on Figure 1 The corresponding implementation flowchart describes the steps for verifying collaborative constraints on train resource occupation, recycling, and warehouse management of potential train sets based on variables related to the connection between preceding and subsequent train numbers.

[0027] Figure 7 It is based on Figure 1 The corresponding embodiment shows a flowchart describing the steps of implementing collaborative constraint verification for train resource occupancy, recycling, and warehouse management of a potential train set.

[0028] Figure 8 It is based on Figure 1 The corresponding embodiment shows a flowchart describing the steps of implementing collaborative constraint verification for train resource occupancy, recycling, and warehouse management of a potential train set.

[0029] Figure 9 It is based on Figure 1 The corresponding embodiment shows a flowchart describing the steps of implementing collaborative constraint verification for train resource occupancy, recycling, and warehouse management of a potential train set. Detailed Implementation

[0030] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided to make the description of this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art. The drawings are merely illustrative of this application and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0031] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more exemplary embodiments. Numerous specific details are provided in the following description to give a full understanding of exemplary embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced with one or more of the specific details omitted, or other methods, components, steps, etc., can be employed. In other instances, well-known structures, methods, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0032] Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0033] See Figure 1 , Figure 1 A flowchart illustrating a method for the coordinated allocation of train resources and warehouses in rail transit scheduling according to an embodiment of this application is provided. The method for the coordinated allocation of train resources and warehouses in rail transit scheduling provided in this application includes:

[0034] Step S110: Adapt to the spatiotemporal characteristics of passenger flow distribution at the station and generate a set of potential train services to meet the passenger flow demand of the target city's rail transit. The potential train services in the set are identified by their starting station and train number.

[0035] Step S120: In the set of potential train numbers, enumerate and filter the previous and next potential train numbers that have the possibility of being connected in terms of time and space. The previous and next potential train numbers form a train number pair.

[0036] Step S130: Construct a connection variable between train numbers for each train number pair. The connection variable between train numbers is used to indicate that the same train is turned back from the previous potential train number to the next potential train number.

[0037] Step S140: Based on the variables of the connection relationship between the preceding and following trains, perform collaborative constraint verification on the train resource occupation, recycling, and warehouse management of the potential train set;

[0038] Step S150: For the set of potential train numbers that satisfy the constraints and the corresponding train control variables, generate a train operation plan and a train scheduling plan adapted to warehouse capacity under the train operation plan.

[0039] These steps are explained in detail below.

[0040] In step S110, historical passenger flow data of each station of the target urban rail transit under different waiting time slots and different directions of travel are processed to digitally describe passenger flow demand, thereby driving the generation of a potential set of train services to meet passenger flow demand.

[0041] In one exemplary embodiment, the digitally described passenger flow demand is converted into the required number of trains, which is then used to construct corresponding station passenger flow matching variables. The potential train numbers mapped by these station passenger flow matching variables are then used to construct a set of potential trains to carry the passenger flow demand. Specifically, the station passenger flow matching variables represent the potential trains mapped within their respective waiting time slots and are assigned to the corresponding stations to carry passenger flow. In other words, the station passenger flow matching variables establish a mapping relationship between passenger flow demand, potential train numbers, and waiting time slots, quantifying the carrying capacity of each potential train at each station.

[0042] Each potential train in the potential train set is identified by its starting station m and train number k, so that it can be accurately indexed and referenced in subsequent constraint verification and scheduling.

[0043] See Figure 2 , Figure 2 It is based on Figure 1 The flowchart described in the corresponding embodiment describes the steps of generating a set of potential train services to meet the passenger flow demand of the target city's rail transit system by adapting the spatiotemporal characteristics of passenger flow at the station.

[0044] The step S110 of this application embodiment, which generates a potential set of train services to meet the passenger flow demand of the target city's rail transit system based on the spatiotemporal distribution of passenger flow at the adapted stations, includes:

[0045] Step S111: For each station of the target urban rail transit, obtain the station passenger flow matching variable that responds to the passenger flow demand in each waiting time slot. The station passenger flow matching variable corresponding to the direction of travel is used to characterize the train assigned to the corresponding waiting time slot, which carries the station passenger flow in the corresponding waiting time slot in the corresponding direction of travel.

[0046] Step S112: Based on the passenger flow matching variables of each station under each waiting time slot and driving direction, determine the set of potential trains that can carry the passenger flow of each station.

[0047] The following is a detailed explanation of these two steps.

[0048] In step S111, for each station and the waiting time slot at each station, a station passenger flow matching variable is constructed in response to the passenger flow demand of the waiting time slot at that station. The station passenger flow matching variable corresponding to the station's travel direction is used to characterize the train numbers allocated to the waiting time slots, so as to achieve the matching between potential train numbers and waiting time slots, and then determine the potential train numbers used to carry the passenger demand of the waiting time slots in this travel direction.

[0049] For example, site passenger flow matching variables are used through variables Representation, Variable The train route lno and direction dir are indicated. A potential train with train number k departs from the originating station m. Its arrival time at station i will fall into the waiting time slot t, and it will carry passengers during the waiting time slot t.

[0050] For station i, for each travel direction dir, the established station passenger flow matching variables are used. Within the corresponding waiting time slice t, determine the set of potential train services to accommodate passenger demand. For each potential train service k included in this set, its station passenger flow matching variable... The value assigned is 1.

[0051] For each station and each waiting time slot at the station, a passenger flow matching variable for the corresponding station is constructed to determine the potential trains that can carry passenger flow for the corresponding waiting time slot.

[0052] For example, the process of constructing station passenger flow matching variables includes: First, for each station's passenger flow demand in different travel directions and waiting time slots, the required number of trains for the station in the corresponding travel direction and waiting time slot is calculated in advance; then, based on the required number of trains for the station in each travel direction and waiting time slot, corresponding binary variables are constructed as station passenger flow matching variables.

[0053] The calculation is expected to be performed on each station and the consecutive waiting time slots at each station, thereby obtaining the number of trains required for each station in different travel directions and in each waiting time slot. For example, the pre-calculation includes: aligning historical passenger flow data at the station and waiting time slots for the consecutively divided waiting time slots after time discretization, obtaining historical passenger flow data for each station in each consecutively divided waiting time slot; splitting the historical passenger flow data for each station in each consecutively divided waiting time slot according to the travel direction, calculating the historical passenger flow for each station in each time slot along different travel directions; and predicting the number of passengers for each station in the corresponding waiting time slot and travel direction based on the historical passenger flow for each station in the consecutively divided waiting time slots along the travel direction, and converting this into the required number of trains.

[0054] In this exemplary embodiment, historical passenger flow data can come from the turnstiles, that is, the entry data of each station with a time stamp is used as historical passenger flow data. In addition, OD data (Origin-Destination Data) will be incorporated to determine the passenger flow of each station in each waiting time slot corresponding to the driving line and driving direction, thereby adapting to the complex scheduling structure under multiple lines and multiple driving directions, and accurately determining the passenger flow generated by each station in each waiting time slot along each driving direction.

[0055] It should be understood that OD data, or OD data combined with arrival data, allows for the determination of passenger flow corresponding to the direction of travel in each waiting time slot at each station. For example, OD data describes passenger travel behavior from the originating station to the destination station. OD data includes at least the arrival station, departure station, arrival time, and departure time. The arrival time can be mapped to a waiting time slot, and the arrival and departure stations are mapped to the travel route and the direction of travel along that route. Therefore, the passenger will be one of the passengers in the mapped waiting time slot and direction of travel at that arrival station. Similarly, the historical passenger flow of a station corresponding to the travel route and direction of travel in each waiting time slot can be determined.

[0056] For each waiting time slot continuously divided at a station, the historical passenger flow in each direction of travel is used to predict the number of passengers along the corresponding direction of travel at that station during this time slot based on spatiotemporal characteristics. The predicted number of passengers along the corresponding direction of travel at that station during this waiting time slot, along with the carrying capacity of a single train, is used to convert the predicted number of passengers into the required number of trains. The carrying capacity of a single train is determined by the target passenger load factor of the target urban rail transit system and the rated passenger capacity of the train.

[0057] Spatiotemporal features include temporal features and spatial features. Temporal features include lag windows (a number of past time slices), weekdays / hours / whether it is a holiday, and event identifiers. Spatial features include weather and traffic to neighboring stations, which will not be listed here.

[0058] The carrying capacity of a single train depends on the operational objectives. It should be understood that the carrying capacity of a single train is determined by the target load factor of the target urban rail transit system and the train's rated passenger capacity; that is, the product of the target load factor and the train's rated passenger capacity. If the operational objective is passenger experience, the carrying capacity of a single train will be reduced by controlling the target load factor, thereby increasing the number of trains. This ensures that passengers do not fill the entire train's capacity while still managing to transport the resulting passenger flow.

[0059] If the operational objective is to reduce operating costs, then the carrying capacity of a single train can be increased by improving the target occupancy rate, thereby ensuring that every train passing through is as full as possible.

[0060] After determining the carrying capacity of a single train in accordance with the operational objectives, the required number of trains can be obtained by calculating the quotient between the number of passengers at the station along the direction of travel in this time slice and the carrying capacity of the single train.

[0061] Therefore, a station passenger flow matching variable can be constructed based on the required number of trains and assigned a value of 1. When the station passenger flow matching variable is set to 1, it is used to indicate that a potential train (m, k) on the train line lno and the train direction dir arrives at station i in the waiting time slot t. Thus, for the same station i, the same train direction dir, and the same waiting time slot t, the number of station passenger flow matching variables with a value of 1 matches the required number of trains for that station in the train direction and waiting time slot.

[0062] In other words, the number of trains required at a station in a certain waiting time slot in a certain direction of travel is carried by all potential trains corresponding to all station passenger flow matching variables with a value of 1 in that waiting time slot.

[0063] Obtain the station passenger flow matching variables for station i under the corresponding driving direction dir and waiting time slice t. Then, the station passenger flow matching variables can be determined. The indicated potential train number (m,k) will stop at station i. Accordingly, the stop indication variable for potential train number (m,k) at station i can be assigned a value of 1.

[0064] At this point, by executing step S111, the station passenger flow matching variable that responds to passenger flow demand and matches each waiting time slot can be obtained for each station of the target urban rail transit, as well as the stop indication variable corresponding to the passenger flow matching variable of this station.

[0065] To further explain, the station passenger flow matching variable for station i under the corresponding travel direction dir and waiting time slot t indicates the potential train number (m,k), which is selected from all potential train numbers that can reach station i within this waiting time slot t, based on the required number of trains.

[0066] It should be added that each time slot is associated with a potential train. Therefore, when constructing station passenger flow matching variables, all potential trains associated with the waiting time slot can be selected.

[0067] In step S112, the passenger flow matching variables of each station in each waiting time slot corresponding to the direction of travel, and the potential train numbers (m,k) mapped to them constitute the potential train number set for the target urban rail transit to meet passenger flow demand. The potential train numbers in the potential train number set are identified by the starting station m and the train number k.

[0068] See Figure 3, Figure 3 It is based on Figure 2 The corresponding embodiment shows a flowchart describing the steps of determining the set of potential train services that can carry station passenger flow based on the station passenger flow matching variables corresponding to each station in each waiting time slot and direction of travel.

[0069] The step S112 provided in this application embodiment, which determines the set of potential train services to carry station passenger flow based on the station passenger flow matching variables corresponding to each station in each waiting time slot and direction of travel, includes:

[0070] S1121, For the waiting time slices of the station in each direction of travel, extract the mapped train number identifier based on the passenger flow matching variables of the corresponding station. The train number identifier includes a combination of the originating station and the train number.

[0071] S1122, construct a set of potential trains for carrying passenger flow demand along the waiting direction during the waiting time slice based on the train number identifier.

[0072] The following is a detailed explanation of these two steps.

[0073] As previously mentioned, each waiting time slot at a station in each direction of travel is determined through the construction of station passenger flow matching variables in step S111, resulting in station passenger flow matching variables corresponding to the station, direction of travel, and waiting time slot. For example, regarding the station passenger flow matching variables... This indicates that, under the route lno and the direction dir, the potential train identified by the originating station m and the train number k will arrive at and stop at station i during the waiting time t.

[0074] Therefore, the station passenger flow matching variables obtained in step S111 can be used. The train number identifier (m,k) mapped to the target urban rail transit system is extracted to determine the potential train numbers that can meet the passenger flow demand at the station within the corresponding travel direction and waiting time slot. Based on the collection of train number identifiers, a set of potential train numbers for the target urban rail transit system at each station, each waiting time slot, and each travel direction can be constructed.

[0075] Based on this, in step S1121, for each waiting time slot in each direction of travel at each station in the target urban rail transit system, the corresponding station passenger flow matching variables are iterated, and the station passenger flow matching variables with a value of 1 are selected. Each station passenger flow matching variable with a value of 1 corresponds to a unique potential train number, and the train number identifier it maps to is determined by the combination of the originating station m and the train number k.

[0076] Specifically, the station passenger flow matching variable is associated with station i, route lno, direction dir, and waiting time slot t. When the station passenger flow matching variable is 1, it means that the potential train identified by the originating station m and train number k arrives at and stops at station i under route lno and direction dir, at waiting time slot t. Therefore, by parsing the station passenger flow matching variable with a value of 1, the corresponding train number identifier (m, k) can be extracted for the station, waiting time slot, and direction of travel.

[0077] In this way, step S1121 realizes the mapping of passenger flow demand description from three dimensions of station time slice to potential train identifiers, providing a clear source of train candidates for the subsequent construction of potential train sets.

[0078] In step S1122, the potential trains are aggregated based on the train number identifiers extracted in step S1121 to construct a set of potential trains to meet the passenger flow demand of the station.

[0079] Specifically, for the same station i, the same driving direction dir, and the same waiting time slice t, based on all the train identifiers (m,k) extracted in step S1121, the corresponding potential trains are included in the currently constructed potential train set for global unified constraint control.

[0080] This aggregation method constructs a set of potential train services that can fully cover the passenger flow capacity requirements of each station in each direction of travel and in each waiting time slot. It also provides a set of basic objects for applying travel section constraints and arrival / departure time constraints to potential train services. This is completely different from the existing method of pre-defining train services based on a fixed timetable. The constructed set of potential train services is derived from the derivation of station passenger flow matching variables, which makes the selection of potential train services directly related to passenger flow demand in the time and space dimensions, thereby improving the adaptability of train operation scheduling to complex passenger flow distribution.

[0081] In another exemplary embodiment, the method for coordinated allocation of train resources and warehouses in rail transit scheduling provided in this application embodiment further includes:

[0082] For potential trains in the potential train set, construct train operation variables and train interval variables to control the running section. The train interval variables indicate the operation of the corresponding potential train and the running section. The train operation variables and train interval variables are used to verify the turn-around connection constraints of train resource occupation.

[0083] Based on this, refer to Figure 4 , Figure 4This is a flowchart illustrating a method for constructing train departure variables and train interval variables for controlling operating intervals from a set of potential trains, according to an exemplary embodiment.

[0084] The steps for constructing train departure variables and train interval variables for controlling the operating interval from the potential train number set provided in this application embodiment include:

[0085] Step S201: For potential trains in the potential train set, construct a train departure variable, which indicates that the potential train is in operation.

[0086] Step S202: Construct a train interval variable corresponding to the potential train number based on the train number departure variable. The train interval variable is used to characterize and control the travel interval of the potential train number.

[0087] In this exemplary embodiment, it should first be explained that the train number departure variable `<lno>` is a Boolean variable used to indicate whether a train (lno, dir, m, k) departs from the originating station `m`, representing the train's direction of travel on line `lno` (dir). The train number / departure variable is used to indicate whether the train has departed. A value of 0 indicates that train k from originating station m has not run; the train operation variable A value of 1 indicates that train number k departs from the originating station m.

[0088] For each potential train in the potential train set, a corresponding train departure variable is constructed to indicate whether that potential train will be put into operation. In other words, the train departure variable... Corresponding to a set (lno, dir, m, k), it is used to indicate whether a potential train numbered k, originating from station m, is selected as an actual train in operation under the train line lno and the train direction dir.

[0089] When the train number operation variable is 0, it means that the potential train with originating station m and train number k does not participate in actual operation, that is, the potential train is not activated; when the train number operation variable is 1, it means that the potential train with originating station m and train number k is selected as the operation train and enters the verification of turnaround connection constraints for train resource occupation.

[0090] Based on the control of train operation variables, a corresponding train interval variable is constructed for each potential train to characterize and control the specific travel interval of that potential train.

[0091] Specifically, train number interval variables This is a binary variable, corresponding to the state of a potential train with train number k operating within the operating interval [m,n]. Here, m represents the originating station of the potential train, and n represents the destination station of the potential train. The train interval variable is used to indicate that the actual operating interval of the potential train is [m,n].

[0092] When the train number interval variable is 1, it means that the corresponding potential train number (m,k) is scheduled as a section train running from the originating station m to the terminal station n; when the train number interval variable is 0, it means that the potential train does not run in the form of a section.

[0093] Since the train number interval variable is used to represent the corresponding operating interval of a potential train number whose operating status is indicated by the train number departure variable, after completing the construction and initialization of the train number departure variable for each potential train number in the potential train number set, the corresponding train number interval variable is further constructed for the potential train number.

[0094] Specifically, based on the originating station and the set of destination stations reachable by each potential train, the possible operating sections of the potential train are enumerated and constructed, and a corresponding train section variable is generated for each possible operating section. In the initialization phase, the train section variable is assigned a value of 1 to indicate that the potential train uses the corresponding operating section as a candidate operating scheme in the initial modeling phase and is put into subsequent constraint verification.

[0095] In step S120, train pairs that may have temporal and spatial connections in the potential train set are enumerated and filtered to obtain train pairs that can be carried by the same train. Then, in step S130, the corresponding front and rear train connection relationship variables can be constructed. That is, the obtained train pairs are used to construct front and rear train connection relationship variables to represent the selection of the same train to turn around and carry the next potential train.

[0096] For a set of potential train services, the construction and values ​​of the variables relating to the preceding and following train services of a train operating a potential train service are jointly determined by conditions such as the departure time of subsequent trains that exist at the terminal station as a turnaround point. The "train-to-train" binding is completed through the variables relating to the preceding and following train services.

[0097] For example, in the execution of step S120, train pairs with turnaround potential can be selected from the potential train set according to the consistency of the destination station and the origin station, as well as the turnaround connectivity of the stations; then, the candidate range is further narrowed based on whether the minimum turnaround time constraint is met between the arrival time (the time when the previous potential train arrives at the destination station) and the departure time (the departure time of the next potential train); and the selected train pairs are processed.

[0098] Then, in step S130, the connection variable between the preceding and following trains for this train pair can be constructed and set to a value of 1. This is the execution process of automatically generating the connection variable between the preceding and following trains in the potential train set, and it is used in the constraint verification in the subsequent step S140 to verify whether the potential train set to which it belongs is a feasible solution.

[0099] For example, in step S140, the train number operation variable of the next potential train and the train number interval variable of the previous potential train constructed based on the aforementioned exemplary embodiment, as well as the connection relationship variable of the train number pairs corresponding to the two potential trains, are used to perform constraint verification for the formation of a turnaround connection between the trains before and after the trains.

[0100] See Figure 5 , Figure 5 It is based on Figure 1 Corresponding implementation in Figure 4 The flowchart describes the method for verifying the collaborative constraints of train resource occupation, recovery, and warehouse management of potential train sets based on the train number operation variables and train number interval variables constructed in the corresponding embodiment and the variables of the connection relationship between preceding and subsequent train numbers.

[0101] The embodiment of this application illustrates a collaborative constraint verification step S140 for train resource occupancy, recovery, and warehouse management of a potential train set based on variables related to the connection between preceding and following train numbers. This step includes:

[0102] Step S141a: For potential trains arriving at the terminal station, when there is a subsequent potential train that continues to depart from the terminal station, obtain the connection relationship variables of the trains before and after the potential trains. The connection relationship variables of the trains before and after the potential trains are used to characterize whether the train turns back from the previous potential train and connects to the subsequent potential train.

[0103] Step S142a: Based on the connection relationship variables of the preceding and following trains, the train number operation variables of the next potential train, and the train number interval variables of the preceding potential train, the constraint verification of the connection between the preceding and following trains is performed, constraining the train to continue running the next potential train after completing the turnaround operation at the terminal station.

[0104] The following is a detailed explanation of these two steps.

[0105] In the constraint verification performed on the set of potential trains in this exemplary embodiment, for each potential train, a connection relationship variable of preceding and following trains with a value of 1 is obtained. Based on the connection relationship variable of preceding and following trains with a value of 1, constraint verification is performed on the train running this potential train to verify that the train can run the next potential train in the opposite direction after completing the turnaround operation at the terminal station.

[0106] Therefore, if both trains are scheduled to run, priority will be given to connecting them by turning around, encouraging trains to turn around at the terminal and continue running as much as possible, thereby improving train utilization.

[0107] In urban rail transit dispatching, trains do not only perform a single trip, but make multiple round trips. If the dispatching does not take into account train turnaround connections, it will lead to a decrease in train utilization and an increase in the number of trains required.

[0108] The exemplary embodiments of this application combine train sequence with train operation by using the connection relationship variables of preceding and following trains, so that the scheduling can be optimized in terms of train quantity and operation mode. It is particularly suitable for scenarios with tight train schedules and limited turnaround station capacity, and reduces the number of trains required by optimizing the connection relationship.

[0109] For example, the constraint verification for the connection between trains performing turnarounds can be achieved through the following formula:

[0110] Sub-constraint verification condition one:

[0111]

[0112]

[0113] Sub-constraint verification condition two:

[0114]

[0115]

[0116] in, These are variables relating to the connection between preceding and following train services; It is the station identifier of station m in the up or down direction of a certain train route; yes Stations on the same route in either the downhill or uphill direction The site identifier; For any potential train (m', l), it represents the shortest time for train k departing from station m in the direction of travel dir, including the departure time at station n and the time it takes to turn around at station n to reach the other direction station m' (s(n) = s(m')). The arrival time of train l departing from station m' in the direction of travel dir may overlap with that of train l arriving at station m'.

[0117] As illustrated by example, sub-constraint verification condition one is used to prohibit trains from making illegal U-turns. Only when there is a subsequent train originating from the terminal station after arriving at the terminal station can the train turn back at the terminal station and continue to run in the opposite direction to execute the subsequent train.

[0118] The second sub-constraint verification condition is used to prioritize the establishment of a U-turn connection. That is, if both trains before and after the U-turn are running, then these two potential trains are prioritized to form a U-turn connection.

[0119] Based on this, furthermore, the train sequence connection variable indicates that after completing the turnaround operation at the terminal station, the train executing the potential train continues to run the next potential train; the execution process of step S140 also includes:

[0120] First, for the previous potential train mapped by the previous train connection relationship variable, obtain its departure time at the terminal station and the arrival time of the corresponding next potential train with the terminal station as the origin station.

[0121] Secondly, by verifying whether the departure time of the previous potential train at the terminal station and the arrival time of the next potential train with the terminal station as the originating station are compatible with the minimum turning time, the turning and reversing time of the train turnaround operation is constrained.

[0122] In this exemplary embodiment, constraint verification of train turnaround and reversal time requirements is performed to ensure the feasibility of the operational sequence of turnaround trains in the potential train set.

[0123] If the variable indicating the connection between train numbers indicates that a train has changed direction and started the next train, that is, the value of the variable indicating the connection between train numbers is 1, then the operation time of the train at the turnaround station needs to be constrained and verified.

[0124] The time interval between the arrival time of the next potential train and the departure time of the previous potential train is constrained to be no less than the minimum turnaround time. The minimum turnaround time is the shortest operation cycle required for the turnaround operation, which covers necessary operations such as driver end change, train inspection and signal system switching.

[0125] This ensures the feasibility of scheduling, meets the minimum operating time requirements of on-site operations, reduces operational risks caused by insufficient turnaround time, and improves the stability and reliability of train operation, which is especially important for terminal stations with obvious bottlenecks in turnaround capacity.

[0126] In this exemplary embodiment, the verification of train turning-off and reversal constraints for two trains changing direction can be achieved using the following formula:

[0127]

[0128]

[0129]

[0130] in, It is the minimum turning time. It is the originating station The train number is Potential train arrival stations Time; It is the time when a potential train with originating station m and train number k departs from station n. It is the constraint elimination constant, the potential train number. This represents the next potential train number.

[0131] When consecutive train services are operated by the same train, the departure time of the preceding potential train service (m,k) at the terminal station n is... , and the next potential train At the starting station Arrival time The difference between the two is not less than the minimum turnaround time required.

[0132] Furthermore, by determining the variables related to the connection between the preceding and following parts... and constraint elimination constant To determine whether this constraint is valid, we need to consider the connection variables between preceding and following trains. When it is 0, the constraint elimination constant This sufficiently large value causes the constraint to be enabled but forcibly disabled to adapt to different train usage scenarios.

[0133] In an exemplary embodiment, the train arrival and storage control variable is used to indicate the destination of train resources after a train service ends, describing whether the corresponding train service enters the warehouse for storage after its operation at the terminal station. If a potential train service is not connected to any subsequent train service and the terminal station is associated with a warehouse, the corresponding train arrival and storage control variable takes the value of 1, indicating that the corresponding train will be withdrawn from operation and recycled by the warehouse, without forming a "suspended train resource".

[0134] Once the connection variables between trains are determined, it becomes possible to identify which arriving trains are not being used subsequently. These trains will need to be taken out of service at the terminal station and stored in a warehouse. Therefore, a train arrival and warehouse entry control variable is introduced for these trains to indicate whether the train has performed a warehouse entry operation.

[0135] In summary, the train arrival and depot entry control variable is used to characterize the recycling of train resources to prevent situations where the whereabouts of trains are unknown after the train operation ends.

[0136] In an exemplary embodiment, the warehouse departure variable is used to characterize whether the corresponding potential vehicle is formed by direct warehouse departure. When there is no feasible preceding and following vehicle connection variable for a potential vehicle as a subsequent potential vehicle, that is, the constructed preceding and following vehicle connection variable has a value of 0, then the potential vehicle is determined to require warehouse departure. Therefore, a corresponding warehouse departure variable can be constructed for the potential vehicle and its value can be set to 1.

[0137] The warehouse departure variable is constructed based on whether the corresponding potential train can be taken over by existing train resources. This indicates whether the potential train will be dispatched directly from the warehouse and represents the new demand for train resources.

[0138] By introducing variables related to the connection between preceding and following trains, and by constructing train arrival and depot entry control variables and depot departure variables on top of these variables, the continuous use and recycling of train resources are controlled. Furthermore, the constraint verification performed in step S140 ensures that the use of train resources within the overall operation scheduling has a complete closed loop, is conflict-free, and does not exceed the limit.

[0139] See Figure 6 , Figure 6 It is based on Figure 1 The corresponding implementation flowchart describes the steps for verifying collaborative constraints on train resource occupation, recycling, and warehouse management of potential train sets based on variables related to the connection between preceding and subsequent train numbers.

[0140] The embodiment of this application illustrates a collaborative constraint verification step S140 for train resource occupancy, recovery, and warehouse management of a potential train set based on variables related to the connection between preceding and following train numbers. This step includes:

[0141] Step S141b: Obtain the warehouse departure variable configured for the next potential train. The warehouse departure variable is used to indicate whether the next potential train is provided by the warehouse for train operation.

[0142] Step S142b: Based on the warehouse departure variable and the connection variable between the preceding and following trains, and combined with the train operation variable indicated by the train interval variable of the next potential train, perform a uniqueness verification on the source of the train running the next potential train, and constrain the train used to run the next potential train to be only the train running the previous potential train, or provided by the warehouse.

[0143] In this exemplary embodiment, constraint verification is performed on the warehouse departure variables and the connection relationship variables between preceding and following trains configured in the potential train set to ensure consistency between scheduling and train operation.

[0144] Based on the connection variable between preceding and following trains, it is determined whether the train for each potential train is a return trip of the preceding train, or whether it needs to be provided by a warehouse. If the connection variable between preceding and following trains is 0, it indicates that there is no direct connection, and the train running the next potential train is not a return trip of the preceding potential train. It is necessary to further determine whether the originating station of the next potential train is connected to a warehouse. If the next potential train does need to be provided by a warehouse, then its corresponding warehouse departure variable is set to 1. This warehouse departure variable is used to instruct the train to perform a train departure action to run the next potential train.

[0145] Correspondingly, the train arrival and entry control variable is 1, to instruct the train of the previous potential train number to perform the entry action.

[0146] Therefore, under the control of variables such as the connection between trains, the warehouse departure variables, and the train arrival and entry control variables, each train can accurately correspond to the actual entry and exit plans in terms of timing, avoiding situations where trains have no available sources or nowhere to park.

[0147] Based on this, the execution process of step S140 further includes: obtaining the train arrival and depot entry control variable configured for the previous potential train, the train arrival and depot entry control variable being used to indicate whether the train running the previous potential train performs the depot entry action after arriving at the terminal station; based on the connection relationship variable between the preceding and following trains and the train arrival and depot entry control variable, and combined with the train interval variable of the previous potential train, performing a uniqueness verification on the destination of the train running the previous potential train, constraining the train used to run the previous potential train to only choose to continue connecting to the next potential train or perform the depot entry action after arriving at the terminal station.

[0148] See Figure 7 , Figure 7 It is based on Figure 1 The corresponding embodiment shows a flowchart describing the steps of implementing collaborative constraint verification for train resource occupancy, recycling, and warehouse management of a potential train set.

[0149] The embodiment of this application illustrates a collaborative constraint verification step S140 for train resource occupancy, recovery, and warehouse management of a potential train set based on variables related to the connection between preceding and following train numbers. This step includes:

[0150] Step S141c: For each train route, obtain the number of trains that can be put into operation daily in each warehouse belonging to the train route. The number of trains corresponds to the connection relationship variable between the preceding and following trains and the train arrival and warehouse entry control variable.

[0151] Step S142c: Based on the total number of trains that can be scheduled on the train line, a constraint verification is performed on the number of trains that can be put into operation in each warehouse each day, and the sum of the number of trains that can be put into operation in each warehouse is constrained to match the total number of trains.

[0152] The following is a detailed explanation of these two steps.

[0153] The constraint verification implemented through these two steps achieves the resource balance constraint verification of the warehouse train allocation, thereby constraining the number of trains that can be put into operation in each warehouse each day.

[0154] For each train line, the number of trains that can be put into operation daily at each warehouse and the total number of trains that can be dispatched on that train line are constrained and verified to ensure that the sum of the number of trains that can be put into operation at each warehouse matches the total number of trains.

[0155] By verifying the constraints of train allocation for the warehouses distributed across each line, the number of trains allocated to all warehouses for each line in the scheduling must be equal to the total number of trains actually available on that line, that is, the total number of train resources available for scheduling on that line. This constitutes the balance constraint of warehouse train allocation.

[0156] For example, constraint verification of train configuration for warehouses distributed along each line can be achieved using the following formula:

[0157]

[0158] in, It refers to the number of trains allocated to a warehouse in the dispatching process for line lno. It represents the total number of trains actually available on line lno.

[0159] In another exemplary embodiment, the method for coordinated allocation of train resources and warehouses in rail transit scheduling provided in this application further includes:

[0160] For each warehouse, the number of trains that can be put into operation daily is configured with variable encoding to determine the number of binary bits used to represent the number of trains in the warehouse; the corresponding binary code is obtained through the determined number of binary bits, and the binary code represents the number of trains that can be put into operation daily in the warehouse.

[0161] The execution process is explained below.

[0162] Based on the aforementioned exemplary embodiment, the number of trains that can be put into operation daily in each warehouse configuration is encoded as variables. Variable encoding uses binary encoding to represent the number of trains in each warehouse with several binary variables. This reduces the complexity of directly using large integer fields in the model solution, maintaining the linearity of the expression while expressing a large integer range with fewer binary variables, making it easier to process.

[0163] The required number of digits is dynamically selected based on the number of trains in the warehouse. Then, a Boolean variable for that digit is created based on the determined number of digits. This Boolean variable is used to indicate whether the digit is enabled. If the value of the Boolean variable is 1, it indicates that the digit is enabled; if the value of the Boolean variable is 0, it indicates that the digit is disabled.

[0164] In summary, each bit in the binary expansion has a unique corresponding Boolean variable. For example, the number of trains configured for each warehouse is obtained by weighted summing the weight corresponding to each bit and the Boolean variable corresponding to that bit.

[0165] Specifically, it can be expressed by the following formula:

[0166]

[0167] in, This refers to the number of trains that can be put into operation daily in the warehouse DP configuration; It is the weight corresponding to each digit. i It is the number of digits; It is a Boolean variable corresponding to the number of digits; This indicates that warehouse dp is located at the starting station m of line lno.

[0168] Therefore, the actual number of trains deployed in each warehouse (dp) per day can be accurately recorded using binary expansion. .

[0169] For example, when a warehouse can store a maximum of 255 trains, an 8-bit binary variable can be used, in which case the value of the bit i can be 0-7.

[0170] In another exemplary embodiment, the execution process of step S140 further includes:

[0171] Based on the number of trains that can be put into operation in the warehouse each day, verify the number of trains in the waiting time slots corresponding to the warehouse at the morning and evening times, and constrain the number of trains in the waiting time slots corresponding to the warehouse at the morning and evening times to be equal to the number of trains that can be put into operation in the warehouse each day.

[0172] In this exemplary embodiment, the number of trains available for operation at each warehouse is the core factor in daily train quantity scheduling, ensuring that each warehouse can effectively be equipped with enough trains at specific times to support the operation and scheduling of the entire network.

[0173] The early start point refers to the daily scheduling start time. At this time, the warehouse needs to ensure that a sufficient number of trains are allocated and dispatched as needed within the corresponding time slice, so that the trains in the warehouse can be put into operation in time at the start time, avoiding delays caused by insufficient train numbers.

[0174] The late point refers to the end of the scheduling process. At this point, it is necessary to ensure that the number of trains in the warehouse at the end of the time slot can support the number of trains that the warehouse needs to put into operation the next day.

[0175] For example, the constraints constructed for an earlier time point are as follows:

[0176]

[0177] in, It represents the number of trains in the warehouse dp within the earlier time segment. This refers to the number of trains that can be put into operation daily at the warehouse, as mentioned above.

[0178] For the later time point, the constraints are as follows:

[0179]

[0180] in, The number of trains in the warehouse dp within the time slice at that time point.

[0181] By verifying the train quantity constraints corresponding to morning and evening times, the number of trains at the morning and evening times is kept consistent, ensuring that the warehouse remains balanced after trains are moved in and out throughout the day. The number of trains stored in the warehouse at the end of the night, through these two constraint verifications, ensures that the entire scheduling achieves a balance between train resource income and expenditure, and guarantees the continuity of daily train allocation to facilitate continued operation the next day, achieving an operational closed loop. This means that the number of trains in each warehouse at the beginning and end of the day is controllable, traceable, and balanced, ensuring the integrity and physical rationality of train flow during scheduling.

[0182] For further details, please refer to [link / reference]. Figure 8 , Figure 8 It is based on Figure 1 The corresponding embodiment shows a flowchart describing the steps of implementing collaborative constraint verification for train resource occupancy, recycling, and warehouse management of a potential train set.

[0183] The embodiment of this application illustrates a collaborative constraint verification step S140 for train resource occupancy, recovery, and warehouse management of a potential train set based on variables related to the connection between preceding and following train numbers. This step includes:

[0184] Step S141d: Based on the operating section indicated by the train interval variable, determine the potential trains associated with the warehouse, and the departure station of the potential trains associated with the warehouse is associated with the warehouse.

[0185] Step S142d: For potential trains associated with the same warehouse, count the number of potential trains that fall into the waiting time slots corresponding to the morning and evening times based on the departure time. The number of potential trains includes the number of potential trains at the morning time and the number of potential trains at the evening time associated with the warehouse's originating station.

[0186] Step S143d: For potential trains falling into the waiting time slot, based on the corresponding preceding and following train connection relationship variables, count the trains that run the previous potential train and turn back to carry the potential train to obtain the number of trains running online in the waiting time slot.

[0187] Step S144d: Based on the number of potential trains related to the warehouse in the waiting time slot and the number of trains running online, calculate the number of trains in the waiting time slot corresponding to the warehouse at the morning and evening times.

[0188] These steps are explained in detail below.

[0189] In step S141d, the actual operating interval of each potential train is determined based on the train interval variable corresponding to the potential train. The originating station of the potential train is determined through the operating interval, which is the station where the warehouse is located.

[0190] This is used to filter out potential trains whose originating station is the warehouse, thus providing a basis for subsequent warehouse-level management and train resource constraint communication.

[0191] In step S142d, for potential trains belonging to the same warehouse, their departure times are counted to determine the number of potential trains in the warehouse that fall into the early time slot corresponding to the waiting time slot, i.e., the number of early time potential trains associated with the warehouse's originating station, and the number of potential trains that fall into the late time slot corresponding to the waiting time slot, i.e., the number of late time potential trains associated with the warehouse's originating station.

[0192] In step S143d, for potential trains falling within the waiting time slot, the situation of trains being carried by the same train turning back is identified and counted, based on the connection variable between preceding and following trains. Specifically, for each potential train, if the corresponding connection variable between preceding and following trains indicates that the potential train is carried by a train that turned back from the previous potential train, then no additional train resources need to be allocated for that potential train. By counting the potential trains that meet the above-mentioned turning back carrying conditions, the number of trains that are already in online operation within the waiting time slot and can directly carry potential trains is obtained.

[0193] In step S144d, the number of potential trains related to the warehouse within the waiting time slot is estimated by combining the number of potential trains within the waiting time slot and the number of online trains determined by step S143d.

[0194] Specifically, by comparing the number of potential train services with the number of trains already in operation, the number of trains that still need to be provided by the warehouse during the corresponding waiting time slots is determined. This yields the actual number of trains the warehouse needs to provide during early and late waiting time slots. The calculated number of trains will serve as input parameters for subsequent verification of warehouse capacity constraints and train resource conservation constraints, verifying whether the warehouse's train resource allocation in different time slots meets operational capacity requirements.

[0195] Through this exemplary embodiment, based on the train interval variable and the connection relationship variable between the preceding and following trains, a quantitative estimation of the train resource occupancy of the warehouse during the critical time slice is realized. This provides a calculable and verifiable basis for the subsequent implementation of warehouse capacity constraints and train resource conservation constraints, thereby effectively improving the engineering feasibility of the rail transit scheduling scheme at the level of train resource and warehouse management.

[0196] In an exemplary embodiment, step S140 includes: based on the warehouse departure variable and train arrival control variable that the potential train number acts on the warehouse, taking the number of trains in the waiting time slot corresponding to the warehouse at the earliest time as the initial state, and performing train resource conservation constraints between adjacent waiting time slots by estimating the number of warehouse trains in each subsequent waiting time slot.

[0197] By conducting this constraint verification, and by tracking and controlling changes in the number of trains in the warehouse, the rationality and continuity of the implemented scheduling are ensured throughout the entire operating cycle.

[0198] The early hour is the starting point of the day's scheduling. The number of trains in the corresponding waiting time slot will serve as the initial state. This state defines the basis for train allocation at the start of scheduling in the warehouse and also provides a starting point for train flow in subsequent time slots.

[0199] As the scheduling process proceeds, the number of trains in the warehouse will change dynamically due to factors such as departure and arrival. In order to ensure the reasonable scheduling of trains, the balance constraint verification of train flow in each time slot is carried out, that is, the reasonableness of the number of trains in each time slot is ensured by planning the number of trains entering and leaving the warehouse in each time slot.

[0200] As the verification of train dynamic flow balance constraints proceeds, each time slice of the entire scheduling cycle will be tracked, and the increase or decrease in the number of trains in the depot will be calculated within each time slice. Specifically, for the depot, the entry and exit of trains will affect the number of trains in the depot. Therefore, it is necessary to track the dynamic changes in the number of trains in the depot in each time slice, and to promptly detect changes during scheduling, thereby effectively avoiding delays and conflicts caused by improper train scheduling.

[0201] For example, taking the number of trains in the warehouse at the earliest point in time as the initial state, for each consecutively divided time slice, the number of trains held by the warehouse in that time slice is tracked and verified based on the warehouse departure variable of the corresponding train number belonging to that time slice and originating from the station, and the arrival and entry variable of the corresponding train number belonging to that time slice and entering the warehouse with this station as the destination.

[0202] Correspondingly, the verification of train dynamic flow balance constraints can be achieved through the following formula:

[0203]

[0204]

[0205] in, It represents the number of vehicles in warehouse dp at time slice t+1; It represents the number of vehicles in warehouse dp during time slice t; This represents the set of trains (m, k) that may depart from warehouse dp at time slice t, along line lno and direction dir. It is a binary variable with a value of 0 or 1, also known as the warehouse departure variable. If the train k departing from the originating station m in the direction of travel of line lno dir comes from the warehouse dp, then it is assigned a value of 1, otherwise it is assigned a value of 0. The warehouse dp is identified by a unique number and is located at a turnaround station. It is a binary variable with a value of 0 or 1, also known as the train arrival and entry variable. If the train (m,k) of line lno and direction dir arrives at station n where warehouse dp is located and enters warehouse dp in time slice t, it is assigned a value of 1; otherwise, it is assigned a value of 0.

[0206] See Figure 9 , Figure 9 It is based on Figure 1 The corresponding embodiment shows a flowchart describing the steps of implementing collaborative constraint verification for train resource occupancy, recycling, and warehouse management of a potential train set.

[0207] The embodiment of this application illustrates a collaborative constraint verification step S140 for train resource occupancy, recovery, and warehouse management of a potential train set based on variables related to the connection between preceding and following train numbers. This step includes:

[0208] Step S141e: Based on the train arrival and depot entry control variable corresponding to the potential train number and the arrival time of the potential train number at the station where the warehouse is located, determine the depot entry waiting time slice corresponding to the potential train number, and construct the train entry time slice mapping variable. The train entry time slice mapping variable is used to instruct the potential train number to perform the train entry action within the mapped waiting time slice.

[0209] Step S142e: By using the train arrival and entry control variable and the train entry time slice mapping variable, the uniqueness constraint verification of the entry behavior of the trains running potential train services is performed, forcing the train to arrive at the station where the warehouse is located and enter the warehouse only within a single time slice.

[0210] This exemplary embodiment constrains and verifies the scheduling of train return trips to the depot to ensure that the return trip behavior of each train conforms to the overall time frame.

[0211] After each operation plan is completed, the train will return to its assigned depot as planned. To ensure the smooth operation of the train returning to the depot, the train arrival and depot entry variables and the constructed train entry time slice mapping variables will be constrained and verified.

[0212] The train entry time slice mapping variable is used to mark whether a train arrives and completes entry into the warehouse within the mapped time slice. For train entry into the warehouse, a uniqueness constraint verification is performed, which forces each train to arrive and enter the warehouse only within a single time slice. This ensures that the train's entry behavior is unique; that is, each train completes entry within only one time slice, and no other time slice or station can repeat the process, avoiding unnecessary scheduling conflicts and resource waste caused by multiple entries.

[0213] The implementation of this constraint verification can optimize train return management, avoid resource waste, and improve the operational efficiency and scheduling feasibility of the rail transit system.

[0214] For example, the constraint verification implemented can be achieved through the following formula:

[0215]

[0216] in, This is a train arrival and entry variable that takes the value 0 or 1. If train k, which departs from the originating station m in the direction of travel of line lno and dir, returns to the warehouse dp after the journey, it is assigned the value 1; otherwise, it is assigned the value 0. The warehouse dp is located at the turnaround station n.

[0217] It is a train entry time slice mapping variable, which is a binary variable with a value of 0 or 1. If the train number (m,k) in the direction of travel of line lno,dir arrives at the station n where warehouse dp is located and enters warehouse dp in time slice t, it is assigned a value of 1, otherwise it is assigned a value of 0.

[0218] This refers to site n being associated with repository dp.

[0219] Furthermore, step S140 also includes: based on the train entry time slice mapping variable and the station passenger flow matching variable, through the consistency verification of the waiting time slices mapped by the two, constraining the corresponding train number to directly switch from the arrival state to the entry state during the waiting time slice.

[0220] In this exemplary embodiment, for a train that has completed all its operational tasks, the time slice, station, and warehouse corresponding to the train's entry into the depot are determined based on the aforementioned constraints. The train's entry into the depot time slice mapping variable identifies the warehouse associated with its station within the determined time slice, thus constraining the train to arrive at the station where the warehouse is located within the allocated unique time slice, thereby completing the entry into the depot.

[0221] To ensure the execution of this inbound operation, a station passenger flow matching variable is used to indicate whether passengers arrive at station n within a specified time slice t. This facilitates Boolean logic operations, reduces scheduling conflicts, and improves model computation efficiency.

[0222] binary variable It is a variable that takes the value 0 or 1 if and only if the arrival time of train number (m,k) at station i in the direction of travel dir is... If the time slice falls within time slice t, it is set to 1; otherwise, it is set to 0.

[0223] It should be understood that the train's entry into the warehouse is tied to a time slice. After the train arrives at the warehouse station within the designated time slice, it needs to complete the entry operation within the same time slice, that is, directly transition from the arrival state to the entry state. By binding the entry operation to the arrival time slice, the temporal consistency and executability of the train's entry process can be effectively guaranteed.

[0224] For example, constraint validation that binds an inbound operation to a time slice can be achieved using the following formula:

[0225]

[0226] This constraint will effectively prevent trains from being stranded outside the depot due to delays or missed time slots, reduce scheduling conflicts in train reception and dispatch at the depot, and improve the safety of trains returning to the depot.

[0227] In summary, by introducing time-slice binding constraints between train arrival at the warehouse station and the warehousing operation, the uniqueness and timing accuracy of train return operations are ensured. This solution effectively combines operational planning with warehouse receiving and dispatching capabilities, improving the executability and operational stability of the scheduling system.

[0228] In one exemplary embodiment, step S140 further includes:

[0229] A baseline constraint verification is performed on the number of warehouse trains in each waiting time slot, constraining the number of warehouse trains in each waiting time slot to be between zero and the upper limit of the number of trains that the warehouse can accommodate.

[0230] In this exemplary embodiment, based on the balance constraint verification of the dynamic flow of trains in the warehouse, a baseline constraint verification of the number of trains in the warehouse is further introduced to ensure that the actual capacity limit and operational safety requirements of the warehouse can be met at any time slice.

[0231] First, it should be noted that the bottom-line control aims to effectively constrain the number of trains in each warehouse in each time slot, thereby achieving upper and lower limits on the number of trains in that time slot.

[0232] The upper limit on the number of trains that can be accommodated is used to avoid exceeding physical storage capacity and ensure safe operation. The lower limit constraint is used to control the number of trains to not be negative, that is, zero is the minimum value, to prevent unreasonable situations in scheduling calculations.

[0233] During the aforementioned constraint verification, continuous variables were established for each warehouse and each time slice. At this point, the upper and lower bound constraints included in the bottom-line constraint verification of this embodiment will be applied. At the warehouse level, each warehouse has its own independent variable to represent its own number of trains; at the time slice level, the operating time of a day is continuously divided into several discrete time slices, and each time slice corresponds to the number of trains in a warehouse.

[0234] In other words, a bottom-line control is applied to the dynamic changes in the number of trains tracked in each time slice. The upper and lower limits of the bottom-line control are directly incorporated into the train scheduling plan and are consistent with the train entry, exit and operation plans.

[0235] It should be understood that if the number of trains, such as the number of trains corresponding to each time slice, exceeds the upper limit of the warehouse's capacity, then the potential set of trains is an infeasible solution and needs to be reconstructed. This is to maintain the verification of trains entering and leaving the warehouse during dynamic changes, ensuring that it conforms to the actual available capacity of the warehouse, effectively preventing scheduling infeasibility caused by warehouse capacity overflow, and at the same time ensuring the safety and feasibility of warehouse train scheduling, providing a solid capacity safety boundary for warehouse resource allocation.

[0236] For example, the bottom-line constraint verification can be achieved using the following formula:

[0237]

[0238] in, It represents the number of trains in warehouse dp at time slice t. It is the maximum number of parking spaces in the warehouse, which is the upper limit for the number of trains it can accommodate.

[0239] With the completion of constraint verification in step S140, step S150 can be used to generate train operation plans and train scheduling plans adapted to warehouse capacity from the set of potential trains that meet the constraints and the corresponding train control variables.

[0240] This enables the mapping from a set of potential train services that satisfy multiple rigid constraints to executable train operation plans and train scheduling plans, thereby ensuring that the generated train operation schemes are feasible and resource-consistent in actual operation.

[0241] In one exemplary embodiment, this application also provides a computer device including a memory, a processor, and a computer program stored in the memory, the processor executing the computer program to implement the steps of the method as described above.

[0242] In one exemplary embodiment, this application also provides a computer program product including a computer program that, when executed by a processor, implements the steps of the method as described above.

[0243] In one exemplary embodiment, this application also provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method as described above.

[0244] Furthermore, although the steps of the method in this application are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0245] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the appended claims.

Claims

1. A method for the coordinated allocation of train resources and warehouses in rail transit scheduling, characterized in that, The method includes: Based on the passenger flow demand of each station of the target city's rail transit system in different directions of travel and during different waiting time periods, determine the required number of trains for each station in the corresponding direction of travel and waiting time period. Based on the number of trains required at each station in each direction of travel and each waiting time slot, a station passenger flow matching variable is constructed. The station passenger flow matching variable establishes a mapping relationship between passenger flow demand and potential trains and waiting time slots, so as to quantify the carrying capacity of each station for each potential train. Based on the station passenger flow matching variables, a set of potential train services to meet passenger flow demand is generated. The potential train services in the set are identified by their originating station and train number. In the set of potential train services, enumerate and filter the previous and next potential train services that have the possibility of being connected in terms of time and space, and the previous and next potential train services form a train service pair. For the train number pair, a connection relationship variable between the preceding and following train numbers is constructed. The connection relationship variable between the preceding and following train numbers is used to indicate that the same train is turned back from the previous potential train number to carry the next potential train number. Based on the connection variables between preceding and following trains, trains that have not been used after arriving at their scheduled trains are identified, and train arrival and depot entry control variables and depot departure variables are constructed. These train arrival and depot entry control variables and depot departure variables control the continuous use and recycling of train resources. Based on the variables of the connection relationship between the preceding and following trains, a collaborative constraint verification is performed on the train resource occupation, recycling, and warehouse management of the potential train set. The constraint verification includes: performing uniqueness verification on the destination of train resources for the previous potential train based on the connection variables between the preceding and following trains and the train arrival and depot entry control variables; Based on the connection variables between preceding and following trains and the train interval variables corresponding to potential trains, warehouse capacity constraint verification and train resource conservation constraint verification are performed. The train interval variables are used to characterize and control the running interval of the potential trains. For the set of potential train numbers that meet the constraints and the corresponding train control variables, generate a train operation plan and a train scheduling plan adapted to warehouse capacity under the train operation plan.

2. The method according to claim 1, characterized in that, The step of generating a potential set of train services to meet the passenger flow demand of the target urban rail transit system based on the station passenger flow matching variables includes: For each station of the target urban rail transit, obtain the station passenger flow matching variable that responds to the passenger flow demand in each waiting time slot. The station passenger flow matching variable corresponding to the direction of travel is used to characterize the train number assigned to the corresponding waiting time slot. The train number carries the station passenger flow in the waiting time slot in the corresponding direction of travel. Based on the passenger flow matching variables of each station under each waiting time slot and driving direction, the set of potential train services that can carry the passenger flow of each station is determined.

3. The method according to claim 1, characterized in that, The method further includes: For the potential trains in the set of potential trains, a train departure variable and a train interval variable are constructed to control the operating section. The train interval variable indicates the departure of the corresponding potential train and the operating section. The train departure variable and the train interval variable are used to verify the turnaround connection constraints of train resource occupation.

4. The method according to claim 3, characterized in that, The step of performing collaborative constraint verification on train resource occupancy, recovery, and warehouse management of the potential train set based on the preceding and following train connection relationship variables includes: For potential trains arriving at the terminal station, when there is a subsequent potential train that departs from the terminal station, the connection relationship variable between the trains that run the potential train is obtained. The connection relationship variable between the trains is used to characterize whether the train turns back from the previous potential train and connects to the subsequent potential train. Based on the connection variables of the preceding and following trains, the train number operation variables of the next potential train, and the train number interval variables of the preceding potential train, the constraint verification of the connection between the preceding and following trains is performed, constraining the train to continue running the next potential train after completing the turnaround operation at the terminal station.

5. The method according to claim 4, characterized in that, The step of performing collaborative constraint verification on train resource occupancy, recovery, and warehouse management of the potential train set based on the preceding and following train connection relationship variables includes: Obtain the warehouse departure variable configured for the next potential train, the warehouse departure variable being used to indicate whether the next potential train is provided by the warehouse for train operation; Based on the warehouse departure variable and the connection variable between the preceding and following trains, and combined with the train operation variable indicated by the train interval variable of the next potential train, a uniqueness verification is performed on the source of the train running the next potential train. The train used to run the next potential train is constrained to be either the train running the previous potential train or provided by the warehouse.

6. The method according to claim 4, characterized in that, The uniqueness verification of the train resource destination for the previous potential train service includes: Obtain the train arrival and depot entry control variables configured for the previous potential train. The train arrival and depot entry control variables are used to indicate whether the train running the previous potential train will perform the depot entry action after arriving at the terminal station. Based on the connection variables between preceding and following trains and the train arrival and depot entry control variables, and combined with the train number interval variables of the previous potential train, the uniqueness verification of the destination of the train running the previous potential train is performed. This constrains the train used to run the previous potential train to only choose to continue connecting to the next potential train or to perform the depot entry action after arriving at the terminal station.

7. The method according to claim 1, characterized in that, The step of performing collaborative constraint verification on train resource occupancy, recovery, and warehouse management of the potential train set based on the preceding and following train connection relationship variables includes: For the previous potential train mapped by the previous train connection relationship variable, obtain its departure time at the terminal station and the arrival time of the corresponding next potential train with the terminal station as the origin station. By verifying whether the departure time of the previous potential train at the terminal station and the arrival time of the subsequent potential train with the terminal station as the originating station are compatible with the minimum turning time, the turning and reversing time of the train turnaround operation is constrained.

8. The method according to claim 1, characterized in that, The step of performing collaborative constraint verification on train resource occupancy, recovery, and warehouse management of the potential train set based on the preceding and following train connection relationship variables includes: For each train route, obtain the number of trains that can be put into operation daily in each warehouse belonging to the train route. The number of trains corresponds to the connection relationship variable between the preceding and following trains and the train arrival and warehouse entry control variable. Based on the total number of trains that can be dispatched on the aforementioned train routes, a constraint verification is performed on the number of trains that can be put into operation daily at each of the aforementioned warehouses, ensuring that the sum of the number of trains that can be put into operation at each of the aforementioned warehouses matches the total number of trains.

9. The method according to claim 8, characterized in that, The step of performing collaborative constraint verification on train resource occupancy, recovery, and warehouse management of the potential train set based on the preceding and following train connection relationship variables includes: Based on the number of trains that can be put into operation at the warehouse each day, the number of trains in the waiting time slots corresponding to the warehouse at the morning and evening times is verified, and the number of trains in the waiting time slots corresponding to the warehouse at the morning and evening times is constrained to be equal to the number of trains that can be put into operation at the warehouse each day.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1-9.

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