Method, device and equipment for generating heavy and empty train operation structure based on traffic demand

Abstract

This application relates to a method, apparatus, and equipment for generating a loaded and empty train operation structure based on transport demand. The method is applied to a railway transport network including multiple transport stations, each corresponding to multiple trains with different load capacities. The method includes: acquiring basic information of each transport station; the basic information includes transport demand information, transport capacity information, and track maintenance window planning information; based on the basic information, determining the corresponding constraints for each transport station; the constraints include at least one of the following: a first transport capacity constraint on track maintenance windows, a second transport capacity constraint on non-track maintenance windows, train quantity constraints, and unloading constraints between adjacent transport stations; and determining the target train operation structure of the railway transport network based on preset loaded car optimization objectives, preset empty car optimization objectives, and the corresponding constraints for each transport station. Using this method, under the premise of meeting transport demand, the transport capacity during track maintenance windows and non-track maintenance windows can be scientifically allocated, improving the rationality of the train operation structure.

Description

Technical Field

[0001] This application relates to the field of railway transportation technology, and in particular to a method, apparatus and equipment for generating a heavy-load empty train operation structure based on transport volume demand. Background Technology

[0002] With the development of railway transportation technology, the railway network has become increasingly complex. In order to ensure the normal operation of the railway transportation system, special train operation interruption periods (i.e., maintenance windows) are set up for the inspection and maintenance of infrastructure such as lines, power supply, and signaling. In contrast, non-maintenance window periods are the periods when the railway normally carries out transportation operations. At the same time, due to the compression effect of maintenance windows on running time, transportation is easily concentrated in non-maintenance window periods, which can easily lead to capacity shortages. Moreover, since maintenance windows are fixed periods reserved in advance, it is easy for construction work to be completed within the maintenance window period, resulting in idle capacity due to the railway being occupied but not used for transportation production.

[0003] In related technologies, a unified planning model is adopted, that is, the same set of fixed rules and the same standard process are used to prepare the train operation plan for the whole day. As a result, in actual operation, there is a mismatch between the allocation of track maintenance window resources and the actual construction needs, which leads to the problem of uncoordinated capacity occupation and station utilization efficiency. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, and equipment for generating a heavy-duty and empty train operation structure based on transport capacity demand, which can optimize the train operation structure while meeting the transport capacity demand, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a method for generating a loaded / empty train operation structure based on transport capacity demand, applied to a railway transport network. The railway transport network includes multiple sequentially connected transport stations, each of which corresponds to multiple types of trains. Different types of trains correspond to different load capacities, and each type of train includes two states: loaded and empty.

[0006] Obtain basic information about each transport station in the railway transport network; wherein, the basic information includes transport demand information, transport capacity information, and track maintenance window planning information;

[0007] Based on the basic information of each transport station, the constraints corresponding to each transport station are determined; the constraints include at least one of the following: first transport volume constraint on maintenance windows, second transport volume constraint on non-maintenance windows, train quantity constraint, and unloading constraint between adjacent transport stations; wherein, the transport volume constraint is used to constrain the relationship between transport volume demand, operating hours, and the number of trains of each type.

[0008] Based on the preset loaded train optimization target, the preset empty train optimization target, and the constraints corresponding to each of the transport stations, the target train operation structure of the railway transport network is determined.

[0009] Secondly, this application also provides a device for generating a loaded / empty train operation structure based on transport capacity demand, applied to a railway transport network. The railway transport network includes multiple sequentially connected transport stations, each of which corresponds to multiple types of trains. Different types of trains correspond to different load capacities, and each type of train includes both loaded and empty states, including:

[0010] The acquisition module is used to acquire basic information of each transport station in the railway transport network; wherein, the basic information includes transport demand information, transport capacity information, and track maintenance window planning information;

[0011] The processing module is used to determine the constraints corresponding to each of the transport stations based on the basic information of each transport station. The constraints include at least one of the following: a first transport volume constraint on maintenance windows, a second transport volume constraint on non-maintenance windows, a train quantity constraint, and an unloading constraint between adjacent transport stations. The transport volume constraint is used to constrain the relationship between transport volume demand, operating hours, and the number of trains of each type.

[0012] The output module is used to determine the target train operation structure of the railway transportation network based on the preset loaded car optimization target, the preset empty car optimization target, and the constraints corresponding to each of the transport stations.

[0013] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method.

[0014] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0015] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described method.

[0016] The aforementioned method, apparatus, and equipment for generating loaded and empty train operation structures based on transport demand, targeting multiple sequentially connected transport stations within a railway transport network, precisely constructs differentiated transport volume constraints suitable for both day and day off, as well as train quantity constraints and unloading constraints at adjacent stations, by integrating basic information such as transport demand, transport capacity, and maintenance window planning of each transport station. This not only aligns with the transport capacity boundaries and station connection requirements under actual railway operation scenarios but also allows for the determination of transport volume allocation for day and day off based on time period restrictions. Furthermore, under the premise of meeting actual operational constraints, independent optimization objectives are set for loaded and empty trains respectively, enabling the generated target train operation structure of the railway transport network to balance the transport efficiency of loaded freight transportation and the allocation efficiency of empty trains, achieving efficient allocation of transport resources and ensuring dynamic matching between transport demand and capacity supply. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is an application environment diagram of a method for generating a heavy-load empty train operation structure based on transport demand in one embodiment.

[0019] Figure 2 This is a flowchart illustrating a method for generating a heavy-load empty train operation structure based on transport capacity demand in one embodiment.

[0020] Figure 3 This is a schematic diagram of the process for generating traffic constraints in one embodiment;

[0021] Figure 4 This is a schematic diagram of the application process of a method for generating a heavy-load empty train operation structure based on transport demand in one embodiment.

[0022] Figure 5 This is a structural block diagram of a heavy-load empty train operation structure generation device based on transport capacity demand in one embodiment.

[0023] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0025] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0026] The method for generating a heavy-load and empty train operation structure based on transport capacity demand provided in this application embodiment can be applied to, for example... Figure 1 The application environment shown is illustrated. Terminal 101 communicates with server 102 via a network. A data storage system can store the data that server 102 needs to process. The data storage system can be integrated onto server 102, or it can be located in the cloud or on another network server.

[0027] Train dispatchers can send a train operation structure generation request for the railway transportation network through terminal 101. The railway transportation network includes multiple sequentially connected transportation stations, each corresponding to multiple types of trains. Different types of trains correspond to different load capacities, and each type of train includes two states: loaded and empty. After receiving the train operation structure generation request, server 102 obtains the basic information of each transportation station in the railway transportation network. The basic information includes transport demand information, transport capacity information, and track window planning information. Based on the basic information of each transportation station, the server determines the corresponding constraints for each transportation station. The constraints include at least one of the following: first transport capacity constraint on track window days, second transport capacity constraint on non-track window days, train quantity constraint, and unloading constraint between adjacent transportation stations. The transport capacity constraint is used to constrain the relationship between transport demand, operating hours, and the number of trains of each type. Based on the preset loaded train optimization target, the preset empty train optimization target, and the constraints corresponding to each transportation station, the server determines the target train operation structure of the railway transportation network and returns the generated target train operation structure to terminal 101 for display.

[0028] In some embodiments, the train dispatcher can pre-compile a railway transport network through terminal 101; for example, at least two transport stations are selected from multiple transport stations, sorted and combined to obtain the railway transport network.

[0029] Terminal 101 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, and projection equipment. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted displays. Head-mounted displays can be virtual reality (VR) devices, augmented reality (AR) devices, and smart glasses. Server 102 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0030] In one exemplary embodiment, such as Figure 2 As shown, a method for generating the operation structure of heavy-duty and empty trains based on transport capacity demand is provided, and this method is applied to... Figure 1 Taking a server as an example, the method is applied to a railway transportation network, which includes multiple sequentially connected transport stations. Each transport station corresponds to multiple types of trains, with different train types corresponding to different load capacities. Each type of train includes two states: loaded and empty. The method includes the following steps 201 to 203. Wherein:

[0031] Step 201: Obtain basic information of each transport station in the railway transport network; the basic information includes transport demand information, transport capacity information, and track maintenance window planning information.

[0032] In some embodiments, the type of train can be classified based on the train's load capacity; for example, the type of train may include a standard train (load capacity 5,000 tons), a 10,000-ton train (load capacity 10,000 tons), a 20,000-ton train (load capacity 20,000 tons), etc.

[0033] In some embodiments, trains with different load capacities are formed by grouping standard trains as basic units; wherein, a standard train is the smallest unit of train division, and a train can be formed by grouping one or more standard trains. Accordingly, the transport capacity of the grouped train is determined by the transport capacity of the standard trains and the number of standard trains grouped together.

[0034] In some embodiments, trains planned to operate within a railway network can only run along the lines included in the railway network. Therefore, under the above operating rules, for each transport station, loaded cars dispatched by that transport station need to be returned empty after completing their transport. That is, for each transport station, the number of loaded cars dispatched and the number of empty cars returned are equal. At the same time, since the transport stations in the railway network are connected sequentially, for the first transport station, its downstream stations can all undertake unloading operations and are all unloading stations. The unloading stations will only split the trains of the upstream stations and will not reassemble the trains of the upstream stations.

[0035] For example, the first transport station is an upstream station of the second transport station. The first transport station dispatches two 10,000-ton trains. After the second transport station unloads some of the cargo, it can split the train into one 10,000-ton train and two standard trains, but it will not combine them into one 20,000-ton train.

[0036] Among them, loaded cars refer to trains that are fully loaded with goods; empty cars refer to trains that are not loaded with goods.

[0037] The freight demand information describes the total amount of goods that a transport station needs to transport via trains with different load capacities during the corresponding operating period. For example, the freight demand information can be the monthly planned freight volume, the weekly planned freight volume, etc.

[0038] Transport capacity information may include delivery capacity and unloading capacity; further, delivery capacity describes the range of trains that a transport station can handle and pass through; unloading capacity describes the range of trains that a transport station can load and unload.

[0039] Track window planning information refers to the schedule of track window periods reserved by the railway transportation network for line maintenance and equipment repair. It can include information on the division of track window days and non-track window days, as well as the start and end times and duration of track windows on track window days.

[0040] In some embodiments, basic information about each transport station in the railway transport network can be obtained by querying the railway management system through the identifier of the railway transport network.

[0041] Step 202: Based on the basic information of each transport station, determine the corresponding constraints for each transport station. The constraints include at least one of the following: first transport volume constraint on maintenance windows, second transport volume constraint on non-maintenance windows, train quantity constraint, and unloading constraint between adjacent transport stations. Among them, the transport volume constraint is used to constrain the relationship between transport volume demand, operating hours, and the number of trains of each type.

[0042] In some embodiments, a track window day refers to a date on which a track window period is planned; the first capacity constraint on a track window day is used to describe the constraint relationship between the total capacity, operating time and number of various types of trains that can be operated on the track window day, and the transportation tasks that need to be completed in the remaining operating time after deducting the track window maintenance time.

[0043] Similarly, non-maintenance windows refer to dates on which no maintenance window period is planned; the second capacity constraint on non-maintenance windows is used to describe the constraint relationship between the total capacity, operating time and number of various types of trains that can be operated on non-maintenance windows, and the transportation tasks that need to be completed during the entire operating time.

[0044] In some embodiments, the capacity constraints can be constructed in a step-by-step manner. For example, firstly, based on the capacity demand of the transport station and the time period available for train operation, the minimum unit transport efficiency that can meet the capacity demand of that time period is calculated. The minimum unit transport efficiency refers to the minimum transport efficiency threshold that needs to be achieved per unit time to meet the predetermined capacity demand within the current available operating period. Subsequently, based on the minimum unit transport efficiency, and combined with the number of trains of different types, the corresponding capacity constraints are further constructed.

[0045] Train quantity constraints refer to the range of trains that a transport station can operate under actual constraints such as the station's scheduling capacity and station configuration.

[0046] The unloading constraint between adjacent transport stations means that the difference in transport volume between adjacent transport stations (upstream and downstream stations) cannot exceed the unloading capacity of the downstream transport station. For example, if the first transport station operates two 10,000-ton trains with a total load of 20,000 tons, and the unloading capacity of the second transport station is 0 (i.e., it has no unloading capacity), then the load capacity of the trains operated by the second transport station should be greater than or equal to 20,000 tons. If the unloading capacity of the second transport station is 10,000 tons, then the load capacity of the trains operated by the second transport station should be greater than or equal to 10,000 tons. This ensures that after unloading at the transport station, the remaining goods can be transported normally.

[0047] In some embodiments, transport capacity information may include a range of train operation numbers and unloading capacity. The range of train operation numbers can be used to determine train quantity constraints, and the unloading capacity can be used to determine unloading constraints between adjacent transport stations.

[0048] In some embodiments, considering that the train operation capacity of a station may differ on maintenance windows and non-maintenance windows, the train quantity constraint may include the train quantity constraint on maintenance windows and non-maintenance windows; similarly, considering that the unloading capacity of a station may differ on maintenance windows and non-maintenance windows, the unloading constraint between adjacent transport stations may include the unloading constraint on maintenance windows and non-maintenance windows.

[0049] Step 203: Based on the preset loaded car optimization target, the preset empty car optimization target, and the corresponding constraints of each transport station, determine the target train operation structure of the railway transport network.

[0050] Among them, the preset loaded vehicle optimization target is the target set for loaded vehicle operation; the preset empty vehicle optimization target is the target set for empty vehicle operation.

[0051] It is worth mentioning that loaded wagons mainly undertake freight transportation tasks. Therefore, the operation of loaded wagons should first consider the freight transportation efficiency and the railway scheduling redundancy capacity, so as to ensure that more turnover can be completed in the same train occupation time under the premise that the railway can pass, thereby improving the freight turnover efficiency. At the same time, the number of trains operated should be minimized to reserve sufficient redundancy space for railway scheduling and improve the flexibility of line operation and scheduling. As for empty wagon operation, its main role is to complete the return operation after unloading. Therefore, the core focus of empty wagon operation optimization is to ensure the safety and controllability of the train operation process, and to ensure the stability of the empty wagon return order and the reliability of the scheduling process.

[0052] Given that loaded train operations and empty train returns have different priorities, optimization orientations for each can be reflected by constructing differentiated objective functions. For example, a weighted multi-objective optimization approach can be adopted, assigning higher weight coefficients to the core priorities of various train types and lower weight coefficients to secondary priorities, thereby constructing a weighted objective function that fits operational needs, and thus forming preset optimization objectives for loaded trains and preset optimization objectives for empty trains.

[0053] For example, for the optimization needs of loaded trains, which are centered on transportation efficiency and scheduling redundancy, a larger weight can be allocated to objectives such as the total number of trains and the number of high-load trains, while a smaller weight can be allocated to secondary objectives such as operational stability. For the optimization needs of empty trains, which are centered on safety and controllability, a larger weight can be allocated to operational safety and scheduling controllability, while the weight of transportation efficiency-related indicators can be reduced accordingly, so that the constructed optimization objectives are matched with the respective operational characteristics of loaded and empty trains.

[0054] In some embodiments, the optimization objective is a multi-objective optimization function. Based on this, the preset loaded car optimization objective and the preset empty car optimization objective can be solved under the constraints corresponding to each transport station. The target train operation structure of the railway transport network can be obtained based on the solution results.

[0055] The aforementioned method for generating a heavy-load and empty train operation structure based on transport demand, for multiple sequentially connected transport stations included in the railway transport network, accurately constructs differentiated transport capacity constraints suitable for both day and day off, as well as train quantity constraints and unloading constraints of adjacent stations, by integrating basic information such as transport capacity demand, transport capacity, and maintenance window planning of each transport station. This not only conforms to the transport capacity boundary and station connection requirements under the actual railway operation scenario, but also determines the transport capacity allocation for day and day off based on time period restrictions. At the same time, under the premise of meeting actual operational constraints, independent optimization objectives are set for heavy-load and empty trains respectively, so that the generated target train operation structure of the railway transport network can take into account the transport efficiency of heavy-load freight transportation and the dispatch efficiency of empty trains, achieve efficient allocation of transport resources, and ensure dynamic matching between transport demand and transport capacity supply.

[0056] In one exemplary embodiment, such as Figure 3 As shown, step 202 includes steps 301 to 305. Wherein:

[0057] Step 301: Based on the track maintenance window planning information of the transport station, determine the unit transport time included in the track maintenance window day, the unit transport time included in the non-track maintenance window day, and the total transport time.

[0058] In some embodiments, the planning period covered by the skylight planning information can be consistent with the time period of the traffic demand; for example, if the operational demand is monthly traffic demand, then the planning period of the skylight planning information is a one-month skylight planning period.

[0059] The unit transportation time is the smallest unit for dividing transportation time, usually set to 1 hour; of course, it can also be set to other time units according to actual needs.

[0060] The unit transportation time included in a skylight day refers to the number of unit transportation times contained in a skylight day; similarly, the unit transportation time included in a non-skylight day refers to the number of unit transportation times contained in a non-skylight day. It can be understood that by counting and statistically analyzing the unit transportation time, it is possible to quantify the actual time available for transportation operations, providing a unified time benchmark for subsequent transportation volume constraint calculations.

[0061] In some embodiments, the track maintenance window planning information for each transport station in the same railway transport network may be the same or different.

[0062] For example, the skylight planning information for a transport station may include: there are 8 skylight days in June, each with a skylight duration of 5 hours, and the skylight period is from midnight to 5 a.m.

[0063] Step 302: Based on the transport station's transport demand information and total transport time, determine the transport demand per unit transport time.

[0064] For example, the total transport demand is determined based on the transport demand information. Then, the ratio of the total transport demand to the total transport time is determined as the transport demand per unit transport time.

[0065] Step 303: Determine the standard train quantity requirement per unit transportation time based on the standard train load included in the transportation capacity information and the volume demand per unit transportation time.

[0066] For example, the ratio of the transport volume demand per unit transport time to the standard train load can be used as the standard train quantity demand per unit transport time.

[0067] Step 304: Based on the unit transportation time included in the maintenance window day, the standard train quantity requirement per unit transportation time, and the mapping relationship between the corresponding train load and standard train load of various types of trains, determine the first transport volume constraint of the transport station on the maintenance window day.

[0068] For example, based on the unit transportation time included in the maintenance window day, the standard train quantity requirement for the maintenance window day can be determined. Then, based on the mapping relationship between the corresponding train load of each type of train and the standard train load, the planned number of trains of each type can be converted into the number of standard trains. In this way, a constraint relationship can be established between the planned number of trains to be operated by the transportation station on the maintenance window day and the standard train quantity requirement. Under this constraint relationship, the transportation station's capacity demand on the maintenance window day can be met, which is the first capacity constraint of the transportation station on the maintenance window day.

[0069] Step 305: Based on the unit transportation time included in non-maintenance windows, the standard train quantity requirement per unit transportation time, and the mapping relationship between the corresponding train load and standard train load of various types of trains, determine the second transport volume constraint of the transport station on non-maintenance windows.

[0070] Similar to step 304, the standard train quantity requirement for non-maintenance window days can be determined based on the unit transportation time included in the non-maintenance window day. Then, based on the mapping relationship between the corresponding train load of each type of train and the standard train load, the planned number of trains of each type can be converted into the number of standard trains. In this way, a constraint relationship can be established between the planned number of trains to be operated by the transportation station on non-maintenance window days and the standard train quantity requirement. Under this constraint relationship, the transportation station's capacity demand on non-maintenance window days can be met, which is the second capacity constraint of the transportation station on non-maintenance window days.

[0071] To facilitate understanding of the above embodiments, the following description will be provided in conjunction with specific embodiments. The first transport volume constraint of the transport station on the maintenance window day can be represented by the following expression:

[0072] .

[0073] Where I represents the set of transport stations included in the railway transport network. , , Q represents the number of the three types of trains (20,000-ton train, 10,000-ton train, and standard train) that operate at transport station i on a maintenance window day. i D represents the monthly transport demand of transport station i, D represents the number of days in the month indicated by the skylight planning information, and T represents the planned skylight time for each skylight day, in hours. β The number of skylight days, The standard train load capacity is the standard train load capacity. The symbol represents rounding up.

[0074] In the above expression, This represents the total skylight hours for the month, expressed in hours. This represents the available time for transportation in the current month, i.e., the total transportation time, expressed in hours. The volume demand per unit of transportation time; The standard train quantity requirement represents the unit of transportation time, i.e., the standard train quantity requirement for 1 hour. This represents the train quantity demand of transport station i during a maintenance window day (a day's transport time is 24 hours minus the maintenance window duration); while the trains actually operated by the transport station include 20,000-ton trains, 10,000-ton trains, and standard trains. Among them, the standard train has a standard train load capacity of 5,000 tons. Therefore, a 20,000-ton train is equivalent to four standard trains, and a 10,000-ton train is equivalent to two standard trains (that is, the mapping relationship between the corresponding train load capacity of each type of train and the standard train load capacity). This represents the number of various types of trains planned to be operated after being converted into standard trains. Obviously, if the above expression is satisfied, the transport capacity of transport station i on the maintenance window day can be met.

[0075] Similarly, the second transport volume constraint of the transport station on non-maintenance days can be represented by the following expression:

[0076] .

[0077] The explanation of the above expression is similar to that of "skylight day," the difference being that... , , Let represent the number of the three types of trains (20,000-ton train, 10,000-ton train, and standard train) that transport station i operates on non-maintenance days, respectively. These will not be elaborated further here. Obviously, if the above expression is satisfied, the transport capacity of transport station i on non-maintenance days can be met.

[0078] In this embodiment, the unit transportation time included in each of the maintenance window days and non-maintenance window days is broken down by using maintenance window planning information. Combined with the transport capacity demand and the standard train load, the train demand per unit time is calculated step by step. Based on the mapping relationship between trains with different loads and standard trains, precise transport capacity constraints for maintenance window days and non-maintenance window days are constructed respectively. This can fit the capacity difference between maintenance periods and normal operation periods, making the transport capacity constraints more in line with the actual operation scenario and improving the rationality and feasibility of train operation planning.

[0079] In some embodiments, determining the constraints corresponding to each transport station based on the basic information of each transport station may further include:

[0080] Based on the range of total train operation numbers included in the transport capacity information of transport stations, the constraints on the total number of train operations are determined.

[0081] For example, if the total number of trains operating at the first transport station ranges from the first number to the second number, then the sum of the number of trains operating of all types must be greater than or equal to the first number and less than or equal to the second number, which is the constraint on the total number of trains operating, where the second number is greater than the first number.

[0082] Based on the transport capacity information of the transport station, the corresponding number range of various types of trains is determined, and the corresponding subclass quantity constraints of each type of train are determined.

[0083] Specifically, the number of trains of each type must be within the range of the corresponding number of trains of that type.

[0084] For example, the trains operated by the first transport station include a first train and a second train. The number of trains operated by the first train is within a first range, and the number of trains operated by the second train is within a second range. Therefore, the number of trains operated by the first train must be within the first range, and the number of trains operated by the second train must be within the second range.

[0085] Based on the total number of trains in operation and the number of trains in each subclass corresponding to various types of trains, the train quantity constraints corresponding to the transport stations are determined.

[0086] For example, the total number of trains and the number of subclasses corresponding to various types of trains can be combined to obtain the train number constraints corresponding to the transport station.

[0087] It is understandable that the trains operating from a transport station need to simultaneously meet the constraints on the total number of trains and the number of each subclass corresponding to each type of train.

[0088] Based on the unloading capacity included in the transport station's transport capacity information, the planned number of trains to be operated at the transport station, and the planned number of trains to be operated at adjacent stations, unloading constraints between adjacent transport stations are determined.

[0089] Unloading capacity can be expressed by the number of cars unloaded; for example, unloading capacity is two 10,000-ton trains.

[0090] For example, unloading constraints between adjacent transport stations can be expressed as: .

[0091] in, This represents the number of trains operating from transport station i+1. This represents the number of trains operating from transport station i. This represents the number of trains that can be unloaded at transport station i+1, i.e., the unloading capacity. Transport station i+1 is the downstream station of transport station i, meaning that goods are transported from transport station i to transport station i+1. It should be noted that when counting the number of trains that have been operated, the types of trains that have been operated must be uniformly the same, such as the number of 20,000-ton trains or the number of 10,000-ton trains.

[0092] In the above embodiments, train quantity constraints are constructed based on the total number of trains operating at each transport station and the number of different types of trains operating. At the same time, unloading constraints are set in combination with the planned number of trains operating at this station and adjacent stations and the unloading capacity. This can accurately match the actual transport capacity of each transport station, making the subsequent train operation plan reasonable and feasible.

[0093] Of course, if the station's transport capacity and unloading capacity are different on maintenance windows and non-maintenance windows, then the train quantity constraints and unloading constraints on maintenance windows and non-maintenance windows can be determined separately based on the transport capacity information corresponding to each maintenance window and non-maintenance window, following the above process.

[0094] In some embodiments, multiple types of trains include a first train, a second train, and a standard train, with the load capacity of the first train, the second train, and the standard train decreasing sequentially; the first train and the second train are obtained by grouping standard trains; the preset heavy-load optimization objectives include a first optimization objective for minimizing the total number of trains in operation, a second optimization objective for maximizing the number of first trains in operation, and a third optimization objective for minimizing the number of standard trains in operation; wherein the priority of the first optimization objective, the second optimization objective, and the third optimization objective gradually decreases.

[0095] For example, different numbers of standard trains can be grouped together to obtain different types of trains; for instance, two standard trains can be grouped together to obtain a second train, and four standard trains can be grouped together to obtain a first train.

[0096] The preset optimization objective for loaded vehicles can be expressed as the following expression:

[0097] .

[0098] Where M is a sufficiently large positive number, and M is used to determine the priority relationship between different optimization objectives; This represents the total number of various types of trains operating from all transport stations in the railway transport network, corresponding to the first optimization objective. This represents the total number of first-time trains operating from each transport station in the railway transport network, corresponding to the second optimization objective. This represents the total number of standard trains operating from each transport station in the railway transport network, corresponding to the third optimization objective.

[0099] As can be seen from the above expression, to make Minimum, required and The smaller, and The larger, at the same time, due to The coefficient is M 2 , The coefficient is M. The coefficient is 1. Obviously, the larger the coefficient, the higher the priority. That is to say, in the above-mentioned preset heavy-load optimization objectives, the first objective is to minimize the total number of trains operated, the second objective is to improve transportation efficiency by operating more high-capacity first trains, and the last objective is to minimize the number of standard trains under the condition of meeting demand. In this way, the fewer the total number of trains, the less capacity is occupied, the larger the scheduling space, and the easier it is to avoid congestion. At the same time, the high-capacity first train can complete more turnover in the same "train occupancy time" compared to the second train or standard train, and is more efficient. Therefore, it is necessary to operate as many first trains as possible. The standard train has higher unit energy consumption, manpower and channel resources occupied compared to other trains. It is better to have as few as possible while ensuring demand.

[0100] In the above embodiments, the preset heavy-load train optimization target prioritizes reducing the total number of trains, maximizing the number of heavy-load trains, and minimizing the number of standard trains. This can fully utilize the capacity advantage of heavy-load trains, improve transportation efficiency, reduce transportation costs, and make train operation planning more in line with transportation efficiency needs.

[0101] In some embodiments, multiple types of trains include a first train, a second train, and a standard train, with the load capacity of the first train, the second train, and the standard train decreasing sequentially; the first train and the second train are obtained by grouping standard trains; the preset empty car optimization objectives include a fourth optimization objective for maximizing the number of second trains, a fifth optimization objective for minimizing the total number of trains, a sixth optimization objective for maximizing the number of first trains, and a seventh optimization objective for minimizing the number of standard trains; wherein the priority of the fourth optimization objective, the fifth optimization objective, the sixth optimization objective, and the seventh optimization objective gradually decreases.

[0102] For example, the preset empty vehicle optimization target can be expressed as the following expression:

[0103] .

[0104] Where M is a sufficiently large positive number, and M is used to determine the priority relationship between different optimization objectives; This represents the total number of second trains operating from each transport station in the railway transport network, corresponding to the fourth optimization objective; This represents the total number of various types of trains operating from each transport station in the railway transport network, corresponding to the fifth optimization objective; This represents the total number of first trains operating from each transport station in the railway transport network, which is the sixth optimization objective. This represents the total number of standard trains operating from each transport station in the railway transport network, which is the seventh optimization objective.

[0105] As can be seen from the above expression, to make Minimum, required and The smaller, and and The larger it is, the higher the coefficients of each term are, in order: M. 3 M 2The coefficients M and 1 represent priorities, with larger coefficients indicating higher priority. In other words, the primary objective in optimizing empty train operations is to maximize the number of second trains while balancing safety and return efficiency. The next objective is to minimize the total number of trains operated to reduce railway occupancy. Then, to improve transport efficiency, the objective is to maximize the number of first trains with higher carrying capacity. Finally, the objective is to minimize the number of standard trains while still meeting demand. This results in fewer standard trains in the second train formation compared to the first, leading to less longitudinal stress, more controllable safety on curved sections of the line, and a more effective control strategy. In addition to being more efficient, the second train has a higher return efficiency compared to the standard train. Therefore, to balance safety and return efficiency, more second trains should be operated. At the same time, the fewer the total number of trains, the less capacity is occupied, the more scheduling space is available, and the easier it is to avoid congestion. Furthermore, the first train with a high load capacity can complete more train returns in the same "train occupancy time" compared to the second train or the standard train. Therefore, it is necessary to operate the first train as much as possible. The standard train has higher energy consumption per unit and occupies more manpower and channel resources than other trains. The fewer the standard trains, the better, while ensuring demand is met.

[0106] In the above embodiments, the preset empty car optimization target prioritizes maximizing the number of second trains, and then controls the total number of trains, maximizes the number of first trains, and minimizes the number of standard trains in sequence. This can adapt to the special scheduling needs of empty car transportation, take into account the safety and efficiency of train return, and optimize the allocation of transportation resources.

[0107] In some embodiments, the target train operation structure of the railway transportation network is determined based on preset loaded car optimization targets, preset empty car optimization targets, and the constraints corresponding to each transport station, including:

[0108] Based on the preset optimization targets for loaded and empty trains, and the corresponding maintenance window constraints for each transport station, the first train operation structure of the railway transport network on the maintenance window day is determined; among them, the maintenance window day constraints include at least the first transport volume constraint.

[0109] Specifically, under the constraints of the maintenance window days corresponding to each transport station, the preset loaded car optimization objective and the preset empty car optimization objective are solved separately to obtain the first train operation structure of the railway transport network on the maintenance window day; wherein, the first train operation structure of the railway transport network on the maintenance window day includes the loaded car operation structure of each transport station on the maintenance window day and the empty car operation structure of each transport station on the maintenance window day.

[0110] In some embodiments, the above-mentioned optimization objectives can be solved by a multi-objective optimization algorithm; the multi-objective optimization algorithm can be Pareto optimality, hierarchical multi-objective genetic algorithm, etc.

[0111] Based on the preset loaded car optimization target, the preset empty car optimization target, and the corresponding non-maintenance day constraints for each transport station, the second train operation structure of the railway transport network on non-maintenance days is determined; among them, the non-maintenance day constraints include at least the second transport volume constraint.

[0112] Specifically, under the constraints of non-maintenance windows for each transport station, the preset loaded car optimization objective and the preset empty car optimization objective are solved separately to obtain the second train operation structure of the railway transport network on non-maintenance windows. The second train operation structure of the railway transport network on non-maintenance windows includes the loaded car operation structure and the empty car operation structure of each transport station on non-maintenance windows.

[0113] Based on the first train operation structure on a maintenance window day and the second train operation structure on a non-maintenance window day, the target train operation structure of the railway transportation network is obtained.

[0114] Specifically, the target train operation structure of the railway transportation network is obtained by combining the first train operation structure on maintenance windows and the second train operation structure on non-maintenance windows.

[0115] In the above embodiments, the corresponding train operation structure is independently solved for different constraints on track maintenance days and non-track maintenance days, combined with the optimization objectives of loaded and empty cars, and then integrated to form the target train operation structure. This can adapt to the differences in transportation restrictions at different times, take into account both track maintenance constraints and transport volume requirements, make train operation planning more in line with actual transportation scenarios, and improve the rationality of railway transportation network scheduling and overall operational efficiency.

[0116] To facilitate understanding, practical applications will be used as examples below. Please refer to [link / reference]. Figure 4 , Figure 4 This application illustrates an application process diagram, including steps S1 to S5, as shown in the embodiment of this application.

[0117] Step S1: Obtain parameters such as station set, monthly planned freight volume, number of days with and without maintenance windows, maintenance window duration, average train load, unloading capacity of each transport station, and upper and lower limits of the number of various types of trains.

[0118] Step S2: Construct an optimization model for non-maintenance window periods, establish the objective function based on the priority of different optimization objectives, and add capacity constraints and train operation quantity constraints; and construct an optimization model for maintenance window periods, establish the objective function based on the priority of different optimization objectives, and add capacity constraints and train operation quantity constraints.

[0119] Step S3: Solve the overall model using a mathematical optimization algorithm. Specifically, under the premise of satisfying various constraints, iteratively optimize to obtain a train operation plan that meets the priority of multiple objectives.

[0120] Step S4: Output the optimal train operation structure scheme to obtain the specific number of loaded and empty trains of each type at each station during the track maintenance window and non-track maintenance window periods.

[0121] Step S5: Adjust the train operation structure based on actual conditions. For example, the optimal train operation structure generated is adaptively adjusted by taking into account factors such as the actual operation of railway transportation sites, sudden transportation demands, and equipment operating status, to ensure that the final operation plan is feasible and adaptable to the site.

[0122] In the above application process, by using comprehensive railway transportation basic parameters, a differentiated optimization model is constructed for the time windows and non-time windows. The mathematical optimization algorithm is used to solve the problem accurately and output the operation plan of various types of trains under the time windows and non-time windows. This can take into account the freight volume demand and the time window operation restrictions, and coordinate the multi-objective optimization needs of heavy car transportation and empty car allocation in an orderly manner, thereby improving the rationality of the train operation structure.

[0123] For example, defining the set of stations included in a railway transport network. Monthly planned freight volume for each station Monthly days Number of days without skylight Number of skylights per day Skylight Average load of the train and the station's unloading capacity Each station has three types of trains: 20,000-ton heavy-haul trains, 10,000-ton heavy-haul trains, and ordinary freight trains (with a load capacity of 5,000 tons). The train type is denoted as 𝑘, where 𝑘=1 represents a 20,000-ton heavy-haul train, 𝑘=2 represents a 10,000-ton heavy-haul train, and 𝑘=3 represents an ordinary freight train. At the same time, based on the actual operation rules of the railway transportation network, the following rules must be followed: the number of loaded cars dispatched by a station is equal to the number of empty cars returned; stations that unload cars do not form new 20,000-ton or 10,000-ton trains.

[0124] The following constraints are determined for the maintenance window days of each station:

[0125] Transportation capacity constraints: .

[0126] Train operation quantity constraints:

[0127] ,and, .

[0128] Train unloading constraints between adjacent stations: .

[0129] in, , , Q represents the number of the three types of trains (20,000-ton train, 10,000-ton train, and standard train) that operate at transport station i on a maintenance window day. i This represents the monthly passenger volume demand of transport station i. This represents the lower limit of the total number of trains operating at transport station i on a maintenance window day. This represents the maximum number of trains that can operate at transport station i on a maintenance window day; This represents the lower limit of the number of type k trains that transport station i can operate on a maintenance window day; This represents the upper limit on the number of type k trains that can operate at transport station i on a maintenance window day; The unloading capacity of the downstream station (i.e., transport station i+1) of transport station i on the maintenance window day; The symbol represents rounding up.

[0130] For days other than skylight days, the following constraints are defined:

[0131] Transportation capacity constraints: .

[0132] Train operation quantity constraints:

[0133] ,and, .

[0134] Train unloading constraints between adjacent stations: .

[0135] in, , , Q represents the number of the three types of trains (20,000-ton train, 10,000-ton train, and standard train) operating at transport station i on non-maintenance days. i This represents the monthly passenger volume demand of transport station i. This represents the lower limit of the total number of trains operating at transport station i on non-maintenance windows. This represents the maximum number of trains that can operate at transport station i on non-maintenance days. This represents the lower limit of the number of type k trains that transport station i can operate on non-maintenance days; This represents the upper limit on the number of type k trains that can operate at transport station i on non-maintenance days; This represents the unloading capacity of the downstream station (i.e., transport station i+1) of transport station i on non-maintenance days.

[0136] For days with sunroofs, the optimization goals for heavy-duty truck operation are as follows:

[0137] .

[0138] The optimization objective for empty train operation is as follows:

[0139]

[0140] Where M is a sufficiently large constant, at least greater than 1.

[0141] For days with sunroofs, the optimization goals for heavy-duty truck operation are as follows:

[0142] .

[0143] The optimization objective for empty train operation is as follows:

[0144] .

[0145] Among the above optimization objectives, the target for loaded trains is first to minimize the total number of trains operated, second to improve transportation efficiency by operating an additional 20,000-ton trains, and finally to minimize the number of general freight trains while meeting demand. On the other hand, empty trains have a high center of gravity and are lightweight. The target for empty trains is first to ensure operational safety. Compared to 20,000-ton empty trains, 10,000-ton empty trains have less longitudinal impact, are more controllable in terms of safety on curved sections of the line, and have more comprehensive control strategies. Therefore, the first consideration is to operate 10,000-ton trains, followed by the total number of trains operated, the number of 20,000-ton trains, and the number of general freight trains.

[0146] For example, the railway network includes stations 1 to 7 connected in sequence, where station 1 is the starting station and station 7 is the ending station, and the seven stations have the same skylight planning information.

[0147] Sunroof planning information can be seen in Table 1 below:

[0148]

[0149] Table 1

[0150] The passenger demand for the seven stations in May is shown in Table 2 below:

[0151]

[0152] Table 2

[0153] The transport capacity information for the seven stations is shown in Table 3 below:

[0154]

[0155] Table 3

[0156] Based on the data in Tables 1 to 3 above, we can construct the traffic volume constraints, train number constraints, and unloading constraints for maintenance windows, as well as the traffic volume constraints, train number constraints, and unloading constraints for non-maintenance windows. Under these constraints, we can jointly solve the optimization objectives for loaded and empty trains to obtain the train operation structure for each station on maintenance windows and for loaded and empty trains on non-maintenance windows. Combining the operation structures of each station, we can obtain the target train operation structure of the railway transportation network, as shown in Table 4 below.

[0157]

[0158] Table 4

[0159] The train operation structure generated through the above process can scientifically allocate capacity during and outside of designated time windows while meeting transport demand, thereby improving the rationality of train operation structure and reducing capacity waste.

[0160] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0161] Based on the same inventive concept, this application also provides an apparatus for generating a heavy-load, empty train operation structure based on traffic demand, for implementing the aforementioned method for generating a heavy-load, empty train operation structure based on traffic demand. The solution provided by this apparatus is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the apparatus for generating a heavy-load, empty train operation structure based on traffic demand provided below can be found in the limitations of the method for generating a heavy-load, empty train operation structure based on traffic demand described above, and will not be repeated here.

[0162] In one exemplary embodiment, such as Figure 5The diagram illustrates a device for generating a loaded / empty train operation structure based on transport demand, applicable to a railway transport network. The railway transport network includes multiple sequentially connected transport stations, each corresponding to multiple types of trains. Different types of trains correspond to different load capacities, and each type of train includes both loaded and empty states. The loaded / empty train operation structure generation device 500 based on transport demand includes:

[0163] The acquisition module 501 is used to acquire basic information of each transport station in the railway transport network; the basic information includes transport demand information, transport capacity information and track maintenance window planning information.

[0164] The processing module 502 is used to determine the corresponding constraints for each transport station based on the basic information of each transport station. The constraints include at least one of the following: the first transport volume constraint on the maintenance window day, the second transport volume constraint on the non-maintenance window day, the train number constraint, and the unloading constraint between adjacent transport stations. The transport volume constraint is used to constrain the relationship between transport volume demand, operating hours, and the number of trains of each type.

[0165] The output module 503 is used to determine the target train operation structure of the railway transportation network based on the preset loaded car optimization target, the preset empty car optimization target, and the corresponding constraints of each transportation station.

[0166] In some embodiments, the processing module 502 is configured to: determine the unit transport time, the unit transport time, and the total transport time included on a day with a maintenance window for the transport station, based on the maintenance window planning information of the transport station; determine the transport volume demand per unit transport time based on the transport station's transport volume demand information and the total transport time; determine the standard train quantity demand per unit transport time based on the transport volume demand per unit transport time and the standard train load included in the transport capacity information; determine the first transport volume constraint of the transport station on a day with a maintenance window, based on the unit transport time included on a day with a maintenance window, the standard train quantity demand per unit transport time, and the mapping relationship between the train load corresponding to each type of train and the standard train load; and determine the second transport volume constraint of the transport station on a day without a maintenance window, based on the unit transport time included on a day without a maintenance window, the standard train quantity demand per unit transport time, and the mapping relationship between the train load corresponding to each type of train and the standard train load.

[0167] In some embodiments, the processing module 502 is configured to: determine a total number of trains constraint based on the range of total trains included in the transport capacity information of the transport station; determine a subclass number constraint corresponding to each type of train based on the range of trains corresponding to each type of train included in the transport capacity information of the transport station; determine a train number constraint corresponding to the transport station based on the total number of trains constraint and the subclass number constraints corresponding to each type of train; and determine unloading constraints between adjacent transport stations based on the unloading capacity included in the transport station's transport capacity information, the planned number of trains to be operated by the transport station, and the planned number of trains to be operated by adjacent stations of the transport station.

[0168] In some embodiments, multiple types of trains include a first train, a second train, and a standard train, with the load capacity of the first train, the second train, and the standard train decreasing sequentially; the first train and the second train are obtained by grouping standard trains; the preset heavy-load optimization objectives include a first optimization objective for minimizing the total number of trains in operation, a second optimization objective for maximizing the number of first trains in operation, and a third optimization objective for minimizing the number of standard trains in operation; wherein the priority of the first optimization objective, the second optimization objective, and the third optimization objective gradually decreases.

[0169] In some embodiments, multiple types of trains include a first train, a second train, and a standard train, with the load capacity of the first train, the second train, and the standard train decreasing sequentially; the first train and the second train are obtained by grouping standard trains; the preset empty car optimization objectives include a fourth optimization objective for maximizing the number of second trains, a fifth optimization objective for minimizing the total number of trains, a sixth optimization objective for maximizing the number of first trains, and a seventh optimization objective for minimizing the number of standard trains; wherein the priority of the fourth optimization objective, the fifth optimization objective, the sixth optimization objective, and the seventh optimization objective gradually decreases.

[0170] In some embodiments, the output module 503 is used to determine the first train operation structure of the railway network on a maintenance window day based on a preset loaded car optimization target, a preset empty car optimization target, and maintenance window day constraints corresponding to each transport station; wherein the maintenance window day constraints include at least a first transport volume constraint; and to determine the second train operation structure of the railway network on non-maintenance window days based on the preset loaded car optimization target, the preset empty car optimization target, and non-maintenance window day constraints corresponding to each transport station; wherein the non-maintenance window day constraints include at least a second transport volume constraint; and to obtain the target train operation structure of the railway network based on the first train operation structure of the railway network on a maintenance window day and the second train operation structure on non-maintenance window days.

[0171] Each module in the aforementioned heavy-duty empty train operation structure generation device based on transport capacity demand can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0172] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores data required for train operation design in the railway transportation network. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for generating a heavy-load / empty train operation structure based on traffic demand.

[0173] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0174] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described above.

[0175] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0176] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described above.

[0177] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0178] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0179] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0180] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for generating a heavy-load empty train operation structure based on transport capacity demand, characterized in that, Applied to a railway transportation network, the railway transportation network includes multiple sequentially connected transportation stations, each transportation station corresponds to multiple types of trains, different types of trains correspond to different load capacities, and each type of train includes two states: loaded and empty. The method includes: Obtain basic information about each transport station in the railway transport network; wherein, the basic information includes transport demand information, transport capacity information, and track maintenance window planning information; Based on the basic information of each transport station, the constraints corresponding to each transport station are determined; the constraints include at least one of the following: first transport volume constraint on maintenance windows, second transport volume constraint on non-maintenance windows, train quantity constraint, and unloading constraint between adjacent transport stations; wherein, the transport volume constraint is used to constrain the relationship between transport volume demand, operating hours, and the number of trains of each type. Based on the preset loaded train optimization target, the preset empty train optimization target, and the constraints corresponding to each of the transport stations, the target train operation structure of the railway transport network is determined.

2. The method according to claim 1, characterized in that, The determination of the constraints corresponding to each of the transport stations based on their basic information includes: Based on the track maintenance window planning information of the transport station, determine the unit transport time included on the track maintenance window day, the unit transport time included on the non-track maintenance window day, and the total transport time. Based on the transport station's capacity demand information and the total transport time, determine the capacity demand per unit transport time; Based on the transport volume demand per unit transport time and the standard train load included in the transport capacity information, the standard train quantity demand per unit transport time is determined. Based on the unit transportation time included in the maintenance window day, the standard train quantity requirement for the unit transportation time, and the mapping relationship between the train load corresponding to each type of train and the standard train load, the first transportation volume constraint of the transportation station on the maintenance window day is determined. Based on the unit transportation time included in the non-maintenance window day, the standard train quantity requirement per unit transportation time, and the mapping relationship between the train load corresponding to each type of train and the standard train load, the second transportation volume constraint of the transportation station on the non-maintenance window day is determined.

3. The method according to claim 1, characterized in that, The determination of the constraints corresponding to each of the transport stations based on their basic information includes: Based on the range of total train operation numbers included in the transportation capacity information of the transportation station, a constraint on the total number of train operation numbers is determined. Based on the range of train operation numbers for each type of train included in the transport capacity information of the transport station, the number constraints of each subclass corresponding to each type of train are determined. Based on the total number of trains operating and the number of subclasses corresponding to each type of train, the train number constraint corresponding to the transport station is determined. Based on the unloading capacity included in the transport station's transport capacity information, the planned number of trains to be operated by the transport station, and the planned number of trains to be operated by the adjacent stations of the transport station, unloading constraints between adjacent transport stations are determined.

4. The method according to claim 1, characterized in that, The various types of trains include a first train, a second train, and a standard train, with the load capacity of the first train, the second train, and the standard train decreasing sequentially; the first train and the second train are obtained by assembling the standard train. The preset heavy-load optimization objectives include a first optimization objective for minimizing the total number of trains in operation, a second optimization objective for maximizing the number of the first trains in operation, and a third optimization objective for minimizing the number of the standard trains in operation. The priorities of the first optimization objective, the second optimization objective, and the third optimization objective gradually decrease.

5. The method according to claim 1, characterized in that, The various types of trains include a first train, a second train, and a standard train, with the load capacity of the first train, the second train, and the standard train decreasing sequentially; the first train and the second train are obtained by assembling the standard train. The preset empty train optimization objectives include a fourth optimization objective for maximizing the number of second trains, a fifth optimization objective for minimizing the total number of trains, a sixth optimization objective for maximizing the number of first trains, and a seventh optimization objective for minimizing the number of standard trains. The priority of the fourth, fifth, sixth, and seventh optimization objectives gradually decreases.

6. The method according to any one of claims 1 to 5, characterized in that, The process of determining the target train operation structure of the railway transportation network based on preset loaded car optimization targets, preset empty car optimization targets, and the respective constraints of each of the transport stations includes: Based on the preset loaded car optimization target, the preset empty car optimization target, and the corresponding maintenance window day constraints for each of the transport stations, the first train operation structure of the railway transport network on the maintenance window day is determined; wherein, the maintenance window day constraints include at least the first transport volume constraint. Based on the preset loaded car optimization target, the preset empty car optimization target, and the non-maintenance day constraints corresponding to each of the transport stations, the second train operation structure of the railway transport network on non-maintenance days is determined; wherein, the non-maintenance day constraints include at least the second transport volume constraint. Based on the first train operation structure of the railway transportation network on maintenance days and the second train operation structure on non-maintenance days, the target train operation structure of the railway transportation network is obtained.

7. A device for generating a heavy-load empty train operation structure based on transport capacity demand, characterized in that, Applied to a railway transportation network, the railway transportation network includes multiple sequentially connected transportation stations, each transportation station corresponds to the operation of multiple types of trains, different types of trains correspond to different load capacities, and each type of train includes two states: loaded and empty. The device includes: The acquisition module is used to acquire basic information of each transport station in the railway transport network; wherein, the basic information includes transport demand information, transport capacity information, and track maintenance window planning information; The processing module is used to determine the constraints corresponding to each of the transport stations based on the basic information of each transport station. The constraints include at least one of the following: a first transport volume constraint on maintenance windows, a second transport volume constraint on non-maintenance windows, a train quantity constraint, and an unloading constraint between adjacent transport stations. The transport volume constraint is used to constrain the relationship between transport volume demand, operating hours, and the number of trains of each type. The output module is used to determine the target train operation structure of the railway transportation network based on the preset loaded car optimization target, the preset empty car optimization target, and the constraints corresponding to each of the transport stations.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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 according to any one of claims 1 to 6.

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