Railway material allocation and path planning method, device, equipment and medium

Abstract

The invention provides a railway material allocation and path planning method and device, equipment and a medium, and relates to the technical field of material allocation, and the method comprises the steps: obtaining transportation network data and supply warehouse data; obtaining a target planning model; based on a preset constraint function in the target planning model, optimizing and adjusting the basic parameters; and planning a transportation path and resource allocation in the emergency scene based on the target parameters. According to the method, the optimization model is constructed through the emergency demand data and the basic parameters, and the material demand and the timeliness requirement in the emergency scene can be effectively quantified, so that the timeliness of emergency response and the sufficiency of material supply are ensured; the basic parameters are optimized through the constraint function in the target planning model, the transportation resource and warehouse resource configuration can be dynamically adjusted, the transportation path and resource allocation can be optimized, all requirements in the emergency response process are ensured to be met, meanwhile, the resource use efficiency is maximized, the emergency response cost is reduced, and the emergency response efficiency is improved. And the emergency management efficiency and flexibility are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of material allocation, and in particular, to a method, device, equipment and medium for railway material allocation and route planning. Background Art

[0002] Material scheduling is a key link in emergency management. Especially in the face of emergencies such as natural disasters, accident disasters, public health events and social security events, efficient emergency material allocation can ensure timely response and minimize the losses and impacts brought by disasters. In the prior art, the transportation network refers to a system composed of various transportation modes and transportation facilities, which is responsible for moving people, goods and services from one place to another in the geographical space. In emergency response, the role of the transportation network is particularly important because it is directly related to the timely arrival of rescue materials, personnel and equipment, as well as the safe evacuation of affected people. However, the existing transportation network is not convenient for providing the shortest or fastest route planning for material allocation, resulting in long material transportation time and affecting the rescue efficiency. Summary of the Invention

[0003] The purpose of the present invention is to provide a method, device, equipment and medium for railway material allocation and route planning to improve the above problems. To achieve the above purpose, the technical solutions adopted by the present invention are as follows:

[0004] In the first aspect, the present application provides a method for railway material allocation and route planning, including:

[0005] Obtain transportation network data and supply warehouse data, and determine a plurality of basic parameters. The transportation network data includes node location information and section connection information, and the supply warehouse data includes material storage categories and material storage quantities;

[0006] Construct an optimization model based on the emergency demand data and a plurality of basic parameters to obtain a target planning model. The emergency demand data is used to characterize the material demand and timeliness demand in the target emergency scenario;

[0007] Based on the preset constraint functions in the target planning model, optimize and adjust the basic parameters to obtain target parameters. The target parameters are the parameters that satisfy each constraint function in the target planning model;

[0008] Plan the transportation route and resource allocation in the emergency scenario based on the target parameters.

[0009] In the second aspect, the present application also provides a device for railway material allocation and route planning, including:

[0010] An acquisition unit, configured to acquire transportation network data and supply warehouse data, and determine a plurality of basic parameters. The transportation network data includes node location information and road section connection information, and the supply warehouse data includes material storage categories and material storage quantities;

[0011] A first construction unit, configured to construct an optimization model based on emergency demand data and a plurality of basic parameters to obtain a target planning model. The emergency demand data is used to represent material demands and timeliness demands in a target emergency scenario;

[0012] An optimization unit, configured to optimize and adjust the basic parameters based on a preset constraint function in the target planning model to obtain target parameters. The target parameters are parameters that satisfy each constraint function in the target planning model;

[0013] A planning unit, configured to plan transportation routes and resource allocation in the emergency scenario based on the target parameters.

[0014] In a third aspect, the present application further provides a railway material allocation and route planning device, including:

[0015] A memory, configured to store a computer program;

[0016] A processor, configured to implement the steps of the railway material allocation and route planning method when executing the computer program.

[0017] In a fourth aspect, the present application further provides a readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned railway material allocation and route planning method are implemented.

[0018] The beneficial effects of the present invention are as follows:

[0019] By constructing an optimization model through emergency demand data and basic parameters, the present invention can effectively quantify material demands and timeliness requirements in an emergency scenario, thereby ensuring the timeliness of emergency response and the sufficiency of material supply. By optimizing the basic parameters through the constraint function in the target planning model, the transportation resources and warehouse resources can be dynamically configured, the transportation routes and resource allocation can be optimized, so as to ensure that all demands in the emergency response process are met, while maximizing the resource utilization efficiency, reducing the emergency response cost, and improving the efficiency and flexibility of emergency management.

[0020] Other features and advantages of the present invention will be described in the subsequent description, and part of them will become obvious from the description, or can be understood by implementing the embodiments of the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in the written description, claims, and drawings. Description of the Drawings

[0021] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the attached drawings required for the embodiments. It should be understood that the following attached drawings only show some embodiments of the present invention, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related attached drawings can also be obtained based on these attached drawings.

[0022] Figure 1 It is a schematic flowchart of the railway material allocation and path planning method described in the embodiments of the present invention;

[0023] Figure 2 It is a schematic structural diagram of the railway material allocation and path planning device described in the embodiments of the present invention;

[0024] Figure 3 It is a schematic structural diagram of the railway material allocation and path planning equipment described in the embodiments of the present invention.

[0025] Reference signs in the figure: 10, acquisition unit; 20, first construction unit; 30, optimization unit; 40, planning unit; 800, railway material allocation and path planning equipment; 801, processor; 802, memory; 803, multimedia component; 804, I / O interface; 805, communication component. Detailed implementation manners

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the attached drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and shown in the attached drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the attached drawings is not intended to limit the scope of the claimed present invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0027] It should be noted that: similar reference signs and letters indicate similar items in the following attached drawings. Therefore, once an item is defined in one attached drawing, it does not need to be further defined and explained in subsequent attached drawings. At the same time, in the description of the present invention, terms such as "first" and "second" are only used for differential description and cannot be understood as indicating or implying relative importance.

[0028] Embodiment 1:

[0029] This embodiment provides a railway material allocation and path planning method.

[0030] See Figure 1 , in the figure, it shows that the method includes step S10, step S20, step S30 and step S40.

[0031] Step S10. Obtain transportation network data and supply warehouse data, and determine a plurality of basic parameters. The transportation network data includes node location information and road segment connection information, and the supply warehouse data includes material storage categories and material storage quantities;

[0032] Specifically, the transportation network data specifically includes node location information and road segment connection information. The node location information is all the node locations involved in the transportation network, such as the demand nodes corresponding to material demands and the supply nodes corresponding to supply warehouses; the road segment connection information is the road segments formed according to the node connection relationship and available for vehicle transportation. In addition, there is an important concept of "bid section" in railway engineering construction. A large-scale railway engineering construction usually includes multiple bid section areas. Each bid section is a geographical area, and each node and road segment belong to a certain bid section. When there is an emergency material demand at a node, materials are usually preferentially allocated from the supply nodes within the bid section.

[0033] Step S20. Based on the emergency demand data and a plurality of basic parameters, construct an optimization model to obtain the target planning model. The emergency demand data is used to characterize the material demand and timeliness demand in the target emergency scenario;

[0034] Specifically, the emergency demand data should include demand nodes, target emergency scenarios, types of material demands, quantities of material demands, and expected arrival times. In this application, the target emergency scenarios are divided into two major categories. One category is road interruption, and the other category is material shortage and vehicle failure. There are some differences in the objective functions and constraint functions constructed for these two major scenarios.

[0035] Specifically, step S20 specifically includes step S21, step S22, step S23 and step S24:

[0036] Step S21. Based on the target emergency scenario and the expected arrival time, construct a calculation formula for the delay time to obtain the delay time function;

[0037] Specifically, step S21 specifically includes step S211, step S212 and step S213:

[0038] Step S211. When the target emergency scenario is road interruption, based on the total transportation path mileage function, the preset driving speed and the expected arrival time, construct the delay time function;

[0039] Specifically, the delay time function constructed in the emergency scenario of road interruption is:

[0040]

[0041] Among them, delay 1 is the delay time function in the emergency scenario of road interruption; is whether the supply warehouse s transports to the emergency demand d 1 through the section (i, j); is the expected arrival time of the emergency demand d 1 ; d (i,j) is the mileage of the section (i, j); ν is the preset driving speed; Demand 1 is the set of emergency demands in the emergency scenario of road interruption, d 1 ∈ Demand 1 ; Arc is the set of sections, (i, j) ∈ Arc; Node s is the set of supply warehouses, s ∈ Node s .

[0042] is a 0-1 variable. When the transportation path from the supply warehouse s to the emergency demand d 1 passes through the section (i, j), it takes the value of 1, otherwise 0.

[0043] Step S212. When the target emergency scenario is material shortage or vehicle failure, determine the interruption node and the loading time corresponding to the interruption node based on the demand node;

[0044] Step S213. Based on the total mileage function of the transportation path, the preset driving speed, the expected arrival time, and the loading time, construct the delay time function;

[0045] Specifically, in the emergency scenario of material shortage or vehicle failure, calculate the delay time function corresponding to each demand node starting from loading at the supply node as:

[0046]

[0047] Among them, is whether the supply warehouse s provides material supply for the emergency demand d 2 ; t s is the loading time of the supply warehouse s; delay 2 is the delay time function in the emergency scenario of material shortage or vehicle failure; is whether the supply warehouse s transports to the emergency demand d 2 through the section (i, j); is the expected arrival time of the emergency demand d 2 ; d (i,j)is the mileage of section (i, j); ν is the preset driving speed; Demand 2 is the set of emergency demands in the emergency scenarios of material shortage or vehicle failure, d 2 ∈ Demand 2 ; Arc is the set of sections, (i, j) ∈ Arc; Node s is the set of supply warehouses, s ∈ Node s .

[0048] is a 0-1 variable, which takes the value of 1 when the supply warehouse s provides material supply for the emergency demand d 2 and 0 otherwise.

[0049] Step S22. Construct the objective function based on the total mileage function of the transportation path and the delay time function;

[0050] Specifically, the total mileage function of the transportation path is:

[0051]

[0052] where Z1 is the total mileage function of the transportation path; indicates whether the transportation from the supply warehouse s to the emergency demand d passes through the section (i, j); d (i,j) is the mileage of section (i, j); Demand is the set of emergency demands, d ∈ Demand; Arc is the set of sections, (i, j) ∈ Arc; Node s is the set of supply warehouses, s ∈ Node s .

[0053] Demand is the total set of emergency demands, that is, this set contains the emergency demands in the three emergency scenarios of road interruption, material shortage and vehicle failure.

[0054] The delay time function for all emergency demands is:

[0055] Z2 = delay 1 + delay 2

[0056] where Z2 is the delay time function; delay 1 is the delay time function in the road interruption emergency scenario; delay 2 is the delay time function in the emergency scenarios of material shortage or vehicle failure.

[0057] The objective function is:

[0058] Z = min(ω1Z1 + ω2Z2)

[0059] Among them, Z is the objective function; Z1 is the total mileage function of the transportation route; Z2 is the delay time function; ω1 and ω2 are weight coefficients.

[0060] By comprehensively considering the delay time and transportation mileage to optimize the route planning, it is ensured that the emergency needs can be met in a timely manner, the overall delay time can be minimized, and the emergency response efficiency can be improved.

[0061] Step S23. Construct constraint functions based on the target emergency scenario, types of material requirements, quantity of material requirements, and basic parameters to obtain multiple target constraint functions;

[0062] Specifically, step S23 specifically includes step S231, step S232, step S233, and step S234:

[0063] Step S231. Construct the first constraint function based on the supply warehouse data, quantity of material requirements, and types of material requirements;

[0064] Specifically, in the emergency scenario of material shortage or vehicle failure, each emergency demand can only be supplied by one supply warehouse, and the quantity supplied by the supply warehouse for the emergency demand must be equal to the material demand quantity of this demand. The corresponding first constraint function is:

[0065]

[0066] Among them, indicates whether supply warehouse s supplies materials for emergency demand d 2 to provide material supply; is the supply quantity provided by supply warehouse s for emergency demand d 2 ; w d2 is the quantity of materials required for emergency demand d 2 ; Demand 2 is the set of emergency demands in the emergency scenario of material shortage or vehicle failure, d 2 ∈Demand 2 ; Node s is the set of supply warehouses, s ∈ Node s .

[0067] is a 0-1 variable. When , it means that emergency demand d 2 is supplied with materials by supply warehouse s; when , it means that emergency demand d 2 is not supplied with materials by supply warehouse s.

[0068] Step S232. Construct the second constraint function based on the supply warehouse data and the set storage quantity of the supply warehouse;

[0069] Specifically, in the emergency scenarios of material shortage or vehicle failure, the objective of the material storage quantity constraint is to ensure that the supply warehouse can meet the material requirements of the emergency demand by considering the material storage quantity in the supply warehouse, the material demand quantity of the emergency demand, and the material quantity provided by the supply warehouse. The corresponding second constraint function is:

[0070]

[0071] Among them, is the supply quantity of material type g provided by supply warehouse s for emergency demand d 2 ; is the storage quantity of material type g in supply warehouse s; Node s is the set of supply warehouses, s ∈ Node s ; Goods is the set of material types, g ∈ Goods; Demand 2 is the set of emergency demands in the emergency scenarios of material shortage or vehicle failure, d 2 ∈ Demand 2 .

[0072] Step S233. Based on the target emergency scenario, the outflow and inflow of materials at intermediate nodes, construct the third constraint function, where the intermediate nodes represent multiple nodes through which materials flow during transportation;

[0073] Specifically, the path continuity constraint ensures that the path of materials from the supply warehouse to the demand node is continuous, that is, materials can be transmitted from the supply warehouse to the demand node along the path. The constraint applicable to Demand 2 is:

[0074]

[0075] Among them, is whether to transport through section (i, j) when supply warehouse s supplies emergency demand d 2 ; is whether to transport through section (j, i) when supply warehouse s supplies emergency demand d 2 ; is whether supply warehouse s provides material supply for emergency demand d 2 ; n s is the supply node corresponding to supply warehouse s; n d represents the demand node corresponding to emergency demand d 2 ; Nod is the set of intermediate nodes, j ∈ Nod; d 2 ∈ Demand 2 ; Arc is the set of sections, (i, j), (j, i) ∈ Arc; Node s is the set of supply warehouses, s ∈ Nodes .

[0076] when i=n s hour, It indicates the outflow of materials from the supply warehouse;

[0077] when i=n d hour, Indicates the inflow of materials arriving at the demand node;

[0078] When i≠n s ,n d hour, It means that the inflow and outflow of materials at the intermediate nodes are balanced and no accumulation occurs.

[0079] Path continuity applies to Demand 1 The constraints are:

[0080]

[0081] in, Supply warehouses to meet emergency needs 1 Whether the supply is transported through the road section (i, j); Supply warehouses to meet emergency needs 1 Whether the supply is transported through the road section (j,i); n v is the node where the vehicle is located in the road interruption scenario; n d Indicates emergency demand 1 Corresponding demand node; Nod is the set of intermediate nodes, j∈Nod; Demand 1 is the set of emergency demands in the road interruption emergency scenario, d 1 ∈Demand 1 ; Arc is a set of road segments, (i,j), (j,i)∈Arc; Node s is the supply warehouse set, s∈Node s .

[0082] when i=n ν hour, It represents the outflow of materials from the node where the vehicle is located in the road interruption scenario;

[0083] when i=n d hour, It represents the inflow of materials arriving at the demand node;

[0084] When i≠n ν ,n d When the road is interrupted, It means that the inflow and outflow of materials at the intermediate nodes are balanced and no accumulation occurs.

[0085] The path continuity constraint ensures the continuity of the path of materials between the supply warehouse and the demand nodes, guaranteeing that the flow of materials in the transportation network is reasonable.

[0086] The constraint function also includes the road interruption constraint, which is used to limit the path selected when transporting materials from the supply warehouse to the demand nodes. The corresponding constraint function is:

[0087]

[0088] where indicates whether the transportation from the supply warehouse s to the emergency demand d passes through the section (i, j); h (i,j) is the traffic status of the section (i, j); M is a positive number; Demand is the set of emergency demands, d ∈ Demand; Arc is the set of sections, (i, j) ∈ Arc; Node s is the set of supply warehouses, s ∈ Node s .

[0089] If the section (i, j) can pass normally, then h (i,j) = 1; if the section (i, j) cannot pass normally, then h (i,j) = 0. M is a sufficiently large positive number used to convert the feasibility constraint conditions into specific numerical limits.

[0090] Step S234. Take the first constraint function, the second constraint function, and the third constraint function as the target constraint functions;

[0091] Specifically, take all the constraint functions as the target constraint functions to construct the goal programming model.

[0092] Step S24. Based on the objective function and multiple target constraint functions, construct the goal programming model;

[0093] Specifically, the objective function and the target constraint functions together constitute the goal programming model.

[0094] Step S30. Based on the preset constraint functions in the goal programming model, optimize and adjust the basic parameters to obtain the target parameters, where the target parameters are the parameters that satisfy each constraint function in the goal programming model;

[0095] Specifically, the target parameters mainly solved by the goal programming model in this application are the transportation path and the resource allocation plan.

[0096] Specifically, step S30 specifically includes step S31, step S32, step S33, step S34, step S35, step S36, step S37, and step S38:

[0097] Step S31. Determine the shortest transportation mileage between all nodes based on the transportation network data, and use it as the target transportation mileage;

[0098] Specifically, step S31 specifically includes steps S311, S312, and S313:

[0099] Step S311. Establish a transportation mileage matrix based on the transportation network data. The transportation mileage matrix is used to represent the transportation mileage between adjacent nodes;

[0100] Step S312. Convert the transportation mileage matrix into a multi-dimensional array, and construct a weighted undirected graph based on the multi-dimensional array to obtain the target weighted undirected graph. The connecting edges between adjacent nodes in the target weighted undirected graph are attached with transportation mileage;

[0101] Step S313. Determine the shortest transportation mileage between all nodes based on the target weighted undirected graph, and use it as the target transportation mileage;

[0102] Specifically, establish a transportation mileage matrix. The rows and columns of the matrix are both nodes. Traverse all the road section connection information. If the road section status is passable, set the transportation mileage between the corresponding two nodes in the transportation mileage matrix, otherwise set it to 0; convert the transportation mileage matrix into a multi-dimensional array, and use the graph function of NetworkX to construct a weighted undirected graph according to the transportation mileage matrix; then use the shortest_path_length function of NetworkX to calculate the shortest path length between all corresponding node pairs in the weighted undirected graph, and use it as the target transportation mileage.

[0103] Step S32. Construct a distance matrix based on the emergency demand data. The rows in the distance matrix represent demand nodes, the columns represent supply nodes, and the elements in the matrix represent the target transportation mileage from the supply node to the demand node. The supply node is the location of the supply warehouse;

[0104] Step S33. Determine the operation: Determine the minimum target transportation mileage in each row of the distance matrix based on the constraint function, and use the supply node corresponding to the minimum target transportation mileage as the candidate node;

[0105] Step S34. Process the operation: Subtract the minimum target transportation mileage corresponding to each row in the distance matrix from the target transportation mileage of each row in the distance matrix to obtain the updated distance matrix;

[0106] Step S35. Compare the operation: Compare the unmatched quantity between the candidate node and the corresponding demand node to obtain a comparison result. The unmatched quantity is used to represent the difference between the material demand of the demand node and the material storage of the candidate node;

[0107] Step S36. Update operation: When the comparison result indicates that the material storage of the candidate node is less than the material demand of the demand node, update the material demand of the demand node and add it back to the distance matrix;

[0108] Step S37. Repeat the determination operation, processing operation, comparison operation, and update operation until the comparison result indicates that the material storage of the candidate supply node is not less than the material demand of the demand node, and then use the candidate node corresponding to the demand node as the target supply node;

[0109] Step S38. Use the target supply node and the corresponding target transportation mileage as target parameters;

[0110] Specifically, in this application, an improved Hungarian algorithm is used to solve the target programming model, and the steps are as follows:

[0111] Step1: Initialize relevant data structures to store the relevant information of each demand node and supply point, providing clear and efficient data access for subsequent operations.

[0112] Step2: For each material type, calculate the total amount of each material type required by all demand nodes, verify whether the total supply amount of each material type meets the demand, and adjust the number of vehicles according to the demand.

[0113] Step3: Initialize a distance matrix, where the size of the matrix is the number of demand nodes multiplied by the number of supply nodes.

[0114] Step4: Traverse all demand nodes and supply nodes, and fill in the target transportation mileage between them into the matrix. If the quantity of a certain supply node is zero, set the distance between this supply node and the demand node to a relatively large value to indicate that this path is inaccessible. For each demand node, select the optimal supply node for matching. Perform the preliminary steps of the Hungarian algorithm by subtracting the minimum value (i.e., the minimum target transportation mileage) of each row, so that the minimum value of each row is zero, thereby simplifying the search for the second smallest value in the subsequent algorithm.

[0115] Step5: By calculating the second smallest value, update the remaining quantity of the supply node and the unmatched quantity of the demand node. If a certain demand quantity is greater than the remaining quantity of the supply node, then this supply node and its remaining supply quantity will be added to the supply list of this demand node, and at the same time, update the unmatched demand quantity of the demand node and the remaining quantity of the supply node. When the quantity of a certain supply node is exhausted, remove it from the matrix list of available supply nodes.

[0116] Step6: Continuously adjust and update the matrix until the demand quantities of all demand nodes are matched to the corresponding supply nodes and all demands are met.

[0117] Step S40. Plan the transportation route and resource allocation in the emergency scenario based on the target parameters;

[0118] Specifically, all the supply nodes corresponding to each demand node form the matching supply point set, which is used as the resource allocation plan correspondingly. The path between the demand node and all its corresponding supply nodes is used as the transportation route corresponding to the resource allocation plan.

[0119] Embodiment 2:

[0120] As Figure 2 shown, this embodiment provides a railway material allocation and path planning device, which includes:

[0121] An acquisition unit 10, configured to acquire transportation network data and supply warehouse data, and determine a plurality of basic parameters. The transportation network data includes node location information and section connection information, and the supply warehouse data includes material storage categories and material storage quantities;

[0122] A first construction unit 20, configured to construct an optimization model based on the emergency demand data and a plurality of basic parameters to obtain a target planning model. The emergency demand data is used to characterize the material demand and time limit demand in the target emergency scenario;

[0123] An optimization unit 30, configured to optimize and adjust the basic parameters based on the preset constraint functions in the target planning model to obtain target parameters. The target parameters are the parameters that satisfy each constraint function in the target planning model;

[0124] A planning unit 40, configured to plan the transportation route and resource allocation in the emergency scenario based on the target parameters.

[0125] In a specific implementation manner disclosed in this application, the first construction unit 20 includes:

[0126] A second construction unit, configured to construct a calculation formula for the delay time based on the target emergency scenario and the expected arrival time to obtain a delay time function;

[0127] A third construction unit, configured to construct an objective function based on the total transportation route mileage function and the delay time function;

[0128] A fourth construction unit, configured to construct constraint functions based on the target emergency scenario, material demand types, material demand quantities, and basic parameters to obtain a plurality of target constraint functions;

[0129] A fifth construction unit, configured to construct a target planning model based on the objective function and the plurality of target constraint functions.

[0130] In a specific implementation manner disclosed in this application, the second construction unit includes:

[0131] The sixth construction unit is used to construct a delay time function based on the total transportation path mileage function, the preset driving speed, and the expected arrival time when the target emergency scenario is a road interruption;

[0132] The first determination unit is used to determine the interruption node and the corresponding loading time of the interruption node based on the demand node when the target emergency scenario is a material shortage or a vehicle breakdown;

[0133] The seventh construction unit is used to construct a delay time function based on the total transportation path mileage function, the preset driving speed, the expected arrival time, and the loading time.

[0134] In a specific implementation manner disclosed in the present application, the fourth construction unit includes:

[0135] The eighth construction unit is used to construct a first constraint function based on the supply warehouse data, the material demand quantity, and the material demand type;

[0136] The ninth construction unit is used to construct a second constraint function based on the supply warehouse data and the set storage capacity of the supply warehouse;

[0137] The tenth construction unit is used to construct a third constraint function based on the target emergency scenario, the outflow and inflow of materials at the intermediate nodes, and the intermediate nodes represent multiple nodes through which the materials flow during transportation;

[0138] The first acting unit is used to use the first constraint function, the second constraint function, and the third constraint function as the target constraint function.

[0139] In a specific implementation manner disclosed in the present application, the optimization unit 30 includes:

[0140] The second acting unit is used to determine the shortest transportation mileage between all nodes based on the transportation network data and use it as the target transportation mileage;

[0141] The eleventh construction unit is used to construct a distance matrix based on the emergency demand data. The rows in the distance matrix represent the demand nodes, the columns represent the supply nodes, and the elements in the matrix represent the target transportation mileage from the supply node to the demand node. The supply node is the location of the supply warehouse;

[0142] The second determination unit is used to perform the operation of determining the minimum target transportation mileage in each row of the distance matrix based on the constraint function and using the supply node corresponding to the minimum target transportation mileage as the candidate node;

[0143] The processing unit is used to perform the operation of subtracting the minimum target transportation mileage corresponding to each row from the target transportation mileage of each row in the distance matrix to obtain the updated distance matrix;

[0144] A comparison unit for performing a comparison operation: comparing the unmet quantity between a candidate node and a corresponding demand node to obtain a comparison result, where the unmet quantity is used to represent the difference between the material demand of the demand node and the material storage of the candidate node;

[0145] An update unit for performing an update operation: when the comparison result indicates that the material storage of the candidate node is less than the material demand of the demand node, updating the material demand of the demand node and adding it back to the distance matrix;

[0146] A repetition unit for repeating the determination operation, the processing operation, the comparison operation, and the update operation until the comparison result indicates that the material storage of the candidate supply node is not less than the material demand of the demand node, and then taking the candidate node corresponding to the demand node as the target supply node;

[0147] A third acting unit for taking the target supply node and the corresponding target transportation mileage as target parameters.

[0148] In a specific embodiment disclosed in the present application, the second acting unit includes:

[0149] A construction unit for constructing a transportation mileage matrix based on transportation network data, where the transportation mileage matrix is used to represent the transportation mileage between adjacent nodes;

[0150] A conversion unit for converting the transportation mileage matrix into a multi-dimensional array and constructing a weighted undirected graph based on the multi-dimensional array to obtain a target weighted undirected graph, where the connecting edges between adjacent nodes in the target weighted undirected graph are attached with transportation mileage;

[0151] A fourth acting unit for determining the shortest transportation mileage between all nodes based on the target weighted undirected graph as the target transportation mileage.

[0152] It should be noted that regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0153] Embodiment 3:

[0154] Corresponding to the above method embodiment, in this embodiment, a railway material allocation and path planning device is also provided. A railway material allocation and path planning device described below can be mutually referred to with a railway material allocation and path planning method described above.

[0155] Figure 3 It is a block diagram of a railway material allocation and path planning device 800 shown according to an exemplary embodiment. As Figure 3As shown, the railway material allocation and path planning device 800 may include: a processor 801 and a memory 802. The railway material allocation and path planning device 800 may also include one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0156] Among them, the processor 801 is used to control the overall operation of the railway material allocation and path planning device 800 to complete all or part of the steps in the above-mentioned railway material allocation and path planning method. The memory 802 is used to store various types of data to support the operation of the railway material allocation and path planning device 800. These data may include, for example, instructions for any application program or method operating on the railway material allocation and path planning device 800, as well as application program-related data, such as contact data, sent and received messages, pictures, audio, video, and so on. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, a magnetic disk, or an optical disc. The multimedia component 803 may include a screen and an audio component. The screen may be a touch screen, for example, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signals may be further stored in the memory 802 or sent through the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the railway material allocation and path planning device 800 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, near field communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them. Accordingly, the communication component 805 may include: a Wi-Fi module, a Bluetooth module, and an NFC module.

[0157] In an exemplary embodiment, the railway material allocation and path planning device 800 may be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components, and is used to execute the above-mentioned railway material allocation and path planning method.

[0158] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided. When the program instructions are executed by a processor, the steps of the above-mentioned railway material allocation and path planning method are implemented. For example, the computer-readable storage medium may be the above-mentioned memory 802 including program instructions, and the above program instructions may be executed by the processor 801 of the railway material allocation and path planning device 800 to complete the above-mentioned railway material allocation and path planning method.

[0159] Embodiment 4:

[0160] Corresponding to the above method embodiment, a readable storage medium is also provided in this embodiment. A readable storage medium described below can be correspondingly referred to with a railway material allocation and path planning method described above.

[0161] A readable storage medium has a computer program stored thereon. When the computer program is executed by a processor, the steps of the railway material allocation and path planning method in the above method embodiment are implemented.

[0162] Specifically, the readable storage medium may be various readable storage media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc that can store program codes.

[0163] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention may have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

[0164] As described above, it is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for railway material allocation and route planning, characterized in that, Including: Obtain transportation network data and supply warehouse data, and determine a plurality of basic parameters. The transportation network data includes node location information and road section connection information, and the supply warehouse data includes material storage categories and material storage quantities; Construct an optimization model based on emergency demand data and a plurality of basic parameters to obtain a target planning model. The emergency demand data is used to characterize the material demand and timeliness demand in the target emergency scenario; Based on the preset constraint functions in the target planning model, optimize and adjust the basic parameters to obtain target parameters. The target parameters are the parameters that satisfy each constraint function in the target planning model; Plan the transportation route and resource allocation in the emergency scenario based on the target parameters.

2. The railway material allocation and path planning method according to claim 1, characterized in that ,Construct an optimization model based on emergency demand data and a plurality of basic parameters to obtain a target planning model. The emergency demand data includes demand nodes, target emergency scenarios, material demand types, material demand quantities, and expected arrival times, including: Based on the target emergency scenario and the expected arrival time, construct a calculation formula for the delay time to obtain a delay time function; Construct an objective function based on the total transportation route mileage function and the delay time function; Based on the target emergency scenario, the material demand types, the material demand quantities, and the basic parameters, construct constraint functions to obtain a plurality of target constraint functions; Construct the target planning model based on the objective function and the plurality of target constraint functions.

3. The railway material allocation and path planning method according to claim 2, characterized in that ,Based on the target emergency scenario and the expected arrival time, construct a calculation formula for the delay time to obtain a delay time function. The emergency scenario includes road interruptions, material shortages, and vehicle failures, including: When the target emergency scenario is a road interruption, construct the delay time function based on the total transportation route mileage function, the preset driving speed, and the expected arrival time; When the target emergency scenario is a material shortage or a vehicle failure, determine the interruption node and the loading time corresponding to the interruption node based on the demand node; Construct the delay time function based on the total transportation route mileage function, the preset driving speed, the expected arrival time, and the loading time.

4. The railway material allocation and path planning method according to claim 3, characterized in that ,Based on the target emergency scenario, the material demand types, the material demand quantities, and the basic parameters, construct constraint functions to obtain a plurality of target constraint functions, including: Construct a first constraint function based on the supply warehouse data, the material demand quantity, and the material demand type; Construct a second constraint function based on the supply warehouse data and the set storage capacity of the supply warehouse; Based on the target emergency scenario, the outflow and inflow of materials at intermediate nodes, construct a third constraint function. The intermediate nodes represent multiple nodes through which materials flow during transportation; Use the first constraint function, the second constraint function, and the third constraint function as the target constraint functions.

5. A railway material allocation and path planning device, characterized in that Including: An acquisition unit for acquiring transportation network data and supply warehouse data, and determining a plurality of basic parameters. The transportation network data includes node location information and road section connection information, and the supply warehouse data includes material storage categories and material storage quantities; The first construction unit is used to construct an optimization model based on the emergency demand data and multiple basic parameters to obtain a target planning model, where the emergency demand data is used to characterize the material demand and timeliness demand in the target emergency scenario; The optimization unit is used to optimize and adjust the basic parameters based on the preset constraint functions in the target planning model to obtain target parameters, where the target parameters are the parameters that satisfy each constraint function in the target planning model; The planning unit is used to plan the transportation route and resource allocation in the emergency scenario based on the target parameters.

6. The railway material allocation and path planning device according to claim 5, characterized in that, The first construction unit includes: The second construction unit is used to construct a calculation formula for the delay time based on the target emergency scenario and the expected arrival time to obtain a delay time function; The third construction unit is used to construct an objective function based on the total transportation route mileage function and the delay time function; The fourth construction unit is used to construct constraint functions based on the target emergency scenario, the types of material demands, the quantity of material demands, and the basic parameters to obtain multiple target constraint functions; The fifth construction unit is used to construct the target planning model based on the objective function and multiple target constraint functions.

7. The railway material allocation and path planning device according to claim 6, wherein The second construction unit includes: The sixth construction unit is used to construct the delay time function based on the total transportation route mileage function, the preset driving speed, and the expected arrival time when the target emergency scenario is a road interruption; The first determination unit is used to determine the interruption node and the corresponding loading time of the interruption node based on the demand node when the target emergency scenario is material shortage or vehicle failure; The seventh construction unit is used to construct the delay time function based on the total transportation route mileage function, the preset driving speed, the expected arrival time, and the loading time.

8. The railway material allocation and path planning device according to claim 7, wherein The fourth construction unit includes: The eighth construction unit is used to construct a first constraint function based on the supply warehouse data, the quantity of material demands, and the types of material demands; The ninth construction unit is used to construct a second constraint function based on the supply warehouse data and the set storage capacity of the supply warehouse; The tenth construction unit is used to construct a third constraint function based on the target emergency scenario, the outflow and inflow of materials at the intermediate nodes, where the intermediate nodes represent multiple nodes through which materials flow during transportation; The first acting unit is used to use the first constraint function, the second constraint function, and the third constraint function as the target constraint functions.

9. A railway material allocation and route planning device, characterized in that, It includes: A memory for storing a computer program; A processor for implementing the steps of the railway material allocation and route planning method according to any one of claims 1 to 4 when executing the computer program.

10. A readable storage medium, characterized in that, A computer program is stored on the readable storage medium, and when the computer program is executed by the processor, the steps of the railway material allocation and route planning method according to any one of claims 1 to 4 are implemented.

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