Multi-modal transport planning method and device, computer equipment and storage medium

Abstract

The application relates to a multimodal transport planning method and device, computer equipment, medium and computer program product. The method comprises the following steps: constructing a coal transport network topology graph according to nodes and transport edges in a coal transport network; the number of nodes and transport edges is multiple, and the transport edge is a transport path between nodes; obtaining node parameters of the nodes and transport parameters of the transport edges in the coal transport network; constructing a target optimization model based on the coal transport network topology graph, the node parameters, the transport parameters and a preset optimization target; determining the transport path, the transport mode corresponding to the transport path and the transport quantity of each type of coal based on the target optimization model. The method can plan a transport path, a transport mode corresponding to each transport path and a transport quantity of different types of coal that can meet the actual demand of a user under the premise of meeting the actual transport condition, so that the actual demand of the user can be met, and the overall transport efficiency is improved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a multimodal transport planning method, apparatus, computer equipment, and computer-readable storage medium. Background Technology

[0002] There is a significant geographical separation between coal resources and major consumption markets. The main production areas are concentrated in the northwest, while the areas with the strongest consumption demand are located in the southeastern coastal regions, thus forming a typical logistics pattern of "coal transported from the west to the east and coal from the north to the south." This pattern results in coal transportation generally characterized by long distances, numerous transshipment points, and high logistics costs.

[0003] In recent years, with the fluctuations in coal transportation volume and the increasing complexity of logistics networks, traditional transportation modes have faced problems such as increased demand for multimodal transport, high transportation costs, and uneven capacity allocation, directly impacting the raw material supply security and operational efficiency of downstream demand-side enterprises. Therefore, in the context of complex logistics networks, how to rationally select coal transportation routes and improve the overall operational efficiency of the transportation system has become a crucial issue that needs to be addressed. Summary of the Invention

[0004] Therefore, it is necessary to provide a multimodal transport planning method, device, computer equipment, computer-readable storage medium, and computer program product that can select coal transport routes according to actual needs under multimodal transport requirements, thereby improving transport efficiency, in order to address the above-mentioned technical problems.

[0005] Firstly, this application provides a multimodal transport planning method, the method comprising:

[0006] Construct a coal transportation network topology graph based on the nodes and transportation edges in the coal transportation network; there are multiple nodes and multiple transportation edges, and the transportation edges are the transportation paths between nodes.

[0007] Obtain the node parameters of nodes and the transportation parameters of transportation edges in the coal transportation network;

[0008] Based on the coal transportation network topology, node parameters, transportation parameters, and preset optimization objectives, a target optimization model is constructed.

[0009] The transportation routes, corresponding transportation modes, and the transportation volumes of various types of coal are determined based on the objective optimization model.

[0010] In one embodiment, a target optimization model is constructed based on the coal transportation network topology, node parameters, transportation parameters, and a preset optimization objective, including:

[0011] Based on the coal transportation network topology, node parameters, and transportation parameters, determine the total transportation cost, total transportation time, total carbon emissions, and total volume fluctuations for various types of coal transportation.

[0012] Construct an objective function with the goal of minimizing total transportation cost, total transportation time, total carbon emissions, and fluctuations in total transportation volume;

[0013] The constraints of the objective optimization function are determined based on the coal transportation network topology, node parameters, and transportation parameters.

[0014] The objective optimization model is obtained by constraining the objective optimization function based on the constraints.

[0015] In one embodiment, at least some of the nodes among the plurality of nodes are transit nodes; the node parameters of each transit node include transit information and unit transit cost, wherein the unit transit cost is the unit cost of converting coal between different transportation modes corresponding to the transit node; the transportation parameters of each transportation edge include transportation information, total transport volume, unit freight rate, transportation distance, interruption probability and interruption cost, wherein the total transport volume is the total transport volume of different types of coal corresponding to the transportation edge, the unit freight rate is the unit freight rate of different transportation modes corresponding to the transportation edge, the transportation distance is the transportation distance of different transportation modes corresponding to the transportation edge, and the interruption probability and interruption cost are the probability and cost of transportation interruption corresponding to each transportation edge;

[0016] Based on the coal transportation network topology, node parameters, and transportation parameters, the total transportation cost is determined, including:

[0017] Based on the total transport volume, unit freight rate, transport distance, and transport information, determine the transport costs of different types of coal transported by different transport methods at each transport edge;

[0018] Based on the total transport volume, unit transshipment cost, and transshipment information, determine the transshipment cost for different types of coal at each transshipment node to be converted between different modes of transport.

[0019] The total interruption cost for each transport edge is determined based on the interruption probability and the interruption cost.

[0020] The total transportation cost is determined based on transportation costs, transshipment costs, and total disruption costs.

[0021] In one embodiment, the transportation parameters further include transportation process time, which is the time taken for different transportation modes to transport along the transportation edge; the node parameters further include transfer time, which is the time taken for different transportation modes to switch between different transportation modes at a transfer node; the total transportation time is determined based on the coal transportation network topology, node parameters, and transportation parameters, including:

[0022] Based on the time of each transportation process and each transportation information, determine the total transportation process time for each transportation edge;

[0023] Based on the total transport volume, the transfer time, and the transfer information, determine the total transfer time for different types of coal to be transferred between different modes of transport at each transfer node;

[0024] The total transportation time is determined based on the total transportation process time and the total transfer time.

[0025] In one embodiment, the transportation parameters further include a first unit carbon emission, which is the unit carbon emission when different transportation modes are transported at a transportation edge; the node parameters further include a second unit carbon emission, which is the unit carbon emission during the transition between different transportation modes at a transit node; the total carbon emissions are determined based on the coal transportation network topology, node parameters, and transportation parameters, including:

[0026] Based on the total transport volume, the carbon emissions per unit, the transport distance, and the transport information, determine the transport carbon emissions of different types of coal transported by different transport methods along each transport route.

[0027] Based on the total transport volume, the carbon emissions of each second unit, and the transshipment information, determine the transshipment carbon emissions of different types of coal converted between different modes of transport at each transshipment node;

[0028] Total carbon emissions are determined based on carbon emissions from transportation and transit.

[0029] In one embodiment, the transportation parameters also include historical average transport volume and actual annual transport volume. The historical average transport volume is the historical average annual transport volume of coal along the transportation edge, and the actual annual transport volume is the actual annual transport volume of different types of coal along the transportation edge. Based on the coal transportation network topology, node parameters, and transportation parameters, the total transport volume fluctuation is determined to include:

[0030] Determine the absolute difference between the historical average transport volume and the actual annual transport volume to determine the fluctuation of total transport volume.

[0031] In one embodiment, determining the transportation route, the corresponding transportation mode, and the transportation volume of various types of coal based on the objective optimization model includes:

[0032] By using transportation routes, transportation methods, and the transportation volume of various types of coal as decision variables, the objective optimization model is solved to obtain multiple solutions and corresponding transportation strategies and objective function values.

[0033] Based on the objective function value, determine the transportation route, the corresponding transportation mode, and the transportation volume of various types of coal among multiple transportation strategies.

[0034] Secondly, this application also provides a multimodal transport planning device, comprising:

[0035] The topology module is used to construct a coal transportation network topology graph based on the nodes and transportation edges in the coal transportation network; there are multiple nodes and multiple transportation edges, and the transportation edges are the transportation paths between nodes.

[0036] The data acquisition module is used to acquire the node parameters of nodes and the transportation parameters of transportation edges in the coal transportation network.

[0037] The modeling module is used to construct a target optimization model based on the coal transportation network topology, node parameters, transportation parameters, and preset optimization objectives.

[0038] The solution module is used to determine the transportation route and the corresponding transportation mode and the transportation volume of various types of coal based on the objective optimization model.

[0039] 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 perform the following steps:

[0040] Construct a coal transportation network topology graph based on the nodes and transportation edges in the coal transportation network; there are multiple nodes and multiple transportation edges, and the transportation edges are the transportation paths between nodes.

[0041] Obtain the node parameters of nodes and the transportation parameters of transportation edges in the coal transportation network;

[0042] Based on the coal transportation network topology, node parameters, transportation parameters, and preset optimization objectives, a target optimization model is constructed.

[0043] The transportation routes, corresponding transportation modes, and the transportation volumes of various types of coal are determined based on the objective optimization model.

[0044] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0045] Construct a coal transportation network topology graph based on the nodes and transportation edges in the coal transportation network; there are multiple nodes and multiple transportation edges, and the transportation edges are the transportation paths between nodes.

[0046] Obtain the node parameters of nodes and the transportation parameters of transportation edges in the coal transportation network;

[0047] Based on the coal transportation network topology, node parameters, transportation parameters, and preset optimization objectives, a target optimization model is constructed.

[0048] The transportation routes, corresponding transportation modes, and the transportation volumes of various types of coal are determined based on the objective optimization model.

[0049] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0050] Construct a coal transportation network topology graph based on the nodes and transportation edges in the coal transportation network; there are multiple nodes and multiple transportation edges, and the transportation edges are the transportation paths between nodes.

[0051] Obtain the node parameters of nodes and the transportation parameters of transportation edges in the coal transportation network;

[0052] Based on the coal transportation network topology, node parameters, transportation parameters, and preset optimization objectives, a target optimization model is constructed.

[0053] The transportation routes, corresponding transportation modes, and the transportation volumes of various types of coal are determined based on the objective optimization model.

[0054] The aforementioned multimodal transport planning method, apparatus, computer equipment, computer-readable storage medium, and computer program product construct a coal transport network topology based on nodes and transport edges in the coal transport network. The number of nodes and transport edges is multiple, with each transport edge representing a transport path between nodes. The method obtains node parameters and transport parameters of the transport edges in the coal transport network. Based on the coal transport network topology, node parameters, transport parameters, and preset optimization objectives, a target optimization model is constructed. Based on the target optimization model, transport paths, corresponding transport modes, and transport volumes of various types of coal are determined. This application abstracts the actual coal transport network into a network topology and, by combining the parameters of each node and transport edge in the coal transport network with preset optimization objectives, determines transport strategies that can meet the optimization objectives. This application comprehensively considers the actual situation where multiple types of coal may be transported simultaneously in a single coal transport network and the optimization objectives desired by the user. Under the premise of conforming to actual transport conditions, it plans transport paths, corresponding transport modes for each transport path, and transport volumes of different types of coal that can meet the user's actual needs, thereby adapting to the user's actual needs and improving overall transport efficiency. Attached Figure Description

[0055] 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.

[0056] Figure 1 This is a diagram illustrating the application environment of a multimodal transport planning method in one embodiment.

[0057] Figure 2 This is a flowchart illustrating a multimodal transport planning method in one embodiment;

[0058] Figure 3 This is a detailed flowchart illustrating the construction of a target optimization model based on a coal transportation network topology, node parameters, transportation parameters, and a preset optimization objective in one embodiment.

[0059] Figure 4 This is a detailed flowchart illustrating how, in one embodiment, the total transportation cost, total transportation time, total carbon emissions, and fluctuations in total transport volume for various types of coal transportation are determined based on the coal transportation network topology, node parameters, and transportation parameters.

[0060] Figure 5 This is a detailed flowchart illustrating the process of determining the total transportation cost, total transportation time, total carbon emissions, and total volume fluctuations for various types of coal transportation based on the coal transportation network topology, node parameters, and transportation parameters, as described in another embodiment.

[0061] Figure 6 This is a detailed flowchart illustrating the process of determining the total transportation cost, total transportation time, total carbon emissions, and total volume fluctuations for various types of coal transportation based on the coal transportation network topology, node parameters, and transportation parameters in another embodiment.

[0062] Figure 7 This is a detailed flowchart illustrating the steps of determining the transportation route, the corresponding transportation mode, and the transportation volume of various types of coal based on the objective optimization model in one embodiment.

[0063] Figure 8 This is a schematic diagram illustrating the implementation process of a multimodal transport planning method in one embodiment;

[0064] Figure 9 This is a structural block diagram of a multimodal transport planning device in one embodiment;

[0065] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0066] 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.

[0067] 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.

[0068] The multimodal transport planning method provided in this application can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on the cloud or other network servers. Terminal 102 constructs a coal transportation network topology map based on the nodes and transportation edges between them. It obtains the node parameters of each node and the transportation parameters of each transportation edge from server 104. Then, based on the coal transportation network topology map, node parameters, transportation parameters, and the optimization objectives set by the user based on actual needs, it constructs a target optimization model. According to this target optimization model, it can determine the transportation path, transportation mode, and various coal transportation volumes that meet the user's actual needs. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, etc. Server 104 can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0069] In one exemplary embodiment, such as Figure 2 As shown, a multimodal transport planning method is provided, which is then applied to... Figure 1 Taking terminal 102 as an example, the explanation includes the following steps 202 and 204. Wherein:

[0070] Step 202: Construct a coal transportation network topology based on the nodes and transportation edges in the coal transportation network.

[0071] In a complete cargo transportation process, to achieve optimal transportation efficiency, the combined use of two or more different modes of transportation (such as rail, road, waterway, and air) is called multimodal transport. Both nodes and transport edges are multiple, with transport edges representing the transportation paths between nodes. Nodes can be locations or facilities with clearly defined geographical locations in the coal transportation network, such as coal mines, railway stations, transshipment bases, ports, power plants, and chemical plants. They represent the starting point (production node), transshipment point (transshipment node), or destination (demand node) in the coal transportation process. Transport edges are the transportation paths connecting two nodes, representing the routes along which coal moves between nodes. These can be rail, road, or waterway channels, and their number, like the number of nodes, is multiple, reflecting the complexity and multi-path characteristics of the coal transportation network.

[0072] In this embodiment, the terminal identifies and extracts node and transport edge information in the coal transportation network, abstracting the coal transportation network into a topological structure. Nodes are represented by geometric points, and transport edges are represented by connecting lines, forming an intuitive coal transportation network topology diagram. The topology diagram does not contain specific transportation parameters or dynamic changes; it only reflects static connection relationships and path layout, providing a basic structure for subsequent parameter integration and model construction.

[0073] Step 204: Obtain the node parameters of the nodes and the transportation parameters of the transportation edges in the coal transportation network.

[0074] Node parameters can be quantitative data describing node attributes, including but not limited to a node's coal processing capacity, storage capacity, operating costs, coal processing time, and carbon emissions during coal processing. For example, a transfer station's maximum coal throughput is 1,000 tons per day, and a port's loading and unloading fee is 50 yuan per ton. Transportation parameters are quantitative data describing the characteristics of transportation edges, including but not limited to transportation distance, transportation time, transportation costs, carbon emissions during transportation, and the availability or capacity limitations of transportation modes. For example, a railway's transportation speed is 80 kilometers per hour, and a waterway's transportation cost is 0.2 yuan per ton-kilometer, reflecting the physical and economic characteristics of the route.

[0075] In this embodiment, the terminal collects node parameters and transportation parameters from the server and associates them with the corresponding nodes and transportation edges in the coal transportation network topology graph. Node parameters cover the key attributes of all nodes, while transportation parameters cover the dynamic and static indicators of all transportation edges. The terminal can standardize the parameters into a format that can be input into the model, such as numerical variables or constraints, through data integration and preprocessing, providing data support for subsequent model construction. The parameter acquisition process is best based on the latest available data to reflect the current state of the network.

[0076] Step 206: Based on the coal transportation network topology, node parameters, transportation parameters, and preset optimization objectives, construct a target optimization model.

[0077] The preset optimization objective can be a pre-defined optimization direction or standard, such as minimizing total transportation cost, minimizing transportation time, or maximizing transportation efficiency, reflecting the specific needs of coal transportation network management. The objective optimization model can be a mathematical optimization model, which may include an objective function, decision variables, and constraints, used to solve for the optimal transportation scheme under a given network structure and parameters.

[0078] In this embodiment, the terminal integrates the coal transportation network topology, node parameters, and transportation parameters, and constructs a target optimization model based on a preset optimization objective. First, the terminal defines decision variables based on the topology, such as path selection variables, transportation mode variables, and coal transportation volume variables. Second, it sets constraints using node parameters and transportation parameters, such as node capacity limits, transportation edge capacity limits, or supply-demand balance constraints. Finally, it establishes an objective function based on the optimization objective, for example, minimizing total cost, incorporating parameters such as transportation cost and node processing cost into the function expression. The model construction process must ensure that all input data is consistent with the topology structure, and that the constraints cover the actual limitations of the network.

[0079] Step 208: Determine the transportation route and the corresponding transportation mode and the transportation volume of various types of coal based on the objective optimization model.

[0080] The transportation path can be a specific route from the starting node to the destination node, consisting of multiple transportation edges connected sequentially. For example, it could be a complete route from coal mine A via railway to transfer station B, and then via waterway to port C. The transportation mode can be the means of transport used on the transportation edge, such as rail, road, or waterway transport, the choice of which is influenced by transportation parameters and optimization objectives. The transportation volume of each type of coal can be the allocation quantity of different coal types along the path, in tons, and must satisfy supply and demand balance.

[0081] In this embodiment, after determining the target optimization model, the terminal applies an optimization algorithm (such as linear programming, integer programming, or a heuristic algorithm) to solve the target optimization model, outputting the optimal transportation route, the corresponding transportation mode for each route, and the transportation volume of each type of coal on each route. The solution process considers all constraints and objective functions to ensure that the result is optimal within the feasible region. The terminal parses the model output into an executable transportation plan, for example, specifying a specific route as "node 1-node 2-node 3", a transportation mode as "railway transportation", a transportation volume of 500 tons for coal 1, and a transportation volume of 300 tons for coal 2. The result must ensure that the total transportation volume meets the supply and demand requirements of each node, without conflict or overflow.

[0082] The aforementioned multimodal transport planning method abstracts the actual coal transport network into a network topology diagram and combines the parameters of each node and transport edge in the coal transport network with preset optimization objectives to determine the transport strategy that can meet the optimization objectives. This application comprehensively considers the actual situation that multiple types of coal may be transported simultaneously in a coal transport network and the optimization objectives that users hope to achieve. Under the premise of conforming to the actual transport situation, it plans transport routes, transport modes corresponding to each transport route, and transport volumes of different types of coal that can meet the actual needs of users, thereby adapting to the actual needs of users and improving the overall transport efficiency.

[0083] In some embodiments, such as Figure 3 As shown, step 206 above includes steps 302 to 308. Wherein:

[0084] Step 302: Based on the coal transportation network topology, node parameters, and transportation parameters, determine the total transportation cost, total transportation time, total carbon emissions, and total volume fluctuations for various types of coal transportation.

[0085] The total transportation cost can be defined as the sum of all expenses incurred in the coal transportation network from origin to destination, including node processing costs and transportation costs at transport edges, such as loading costs at coal mines and transportation costs on railway sections. The total transportation time can be defined as the total time required to transport coal from origin to destination, including processing and waiting times at each node and transit time at transport edges. The total carbon emissions can be defined as the sum of greenhouse gas emissions, such as carbon dioxide, directly or indirectly generated at each transport edge due to the use of different transportation modes and during transshipment at each node throughout the entire transportation process. The total transport volume fluctuation can be defined as the degree of instability or variation in coal transport volume over time, reflecting the stability level of the transportation network.

[0086] In this embodiment, the terminal, based on the constructed coal transportation network topology, combines the cost, time, carbon emission coefficient and processing capacity data in the node parameters, as well as the unit cost, time, carbon emission coefficient and capacity data in the transportation parameters, and uses mathematical calculations to determine the total transportation cost, total transportation time, total carbon emissions and total volume fluctuation of various types of coal transportation in the entire network.

[0087] Step 304: Construct an objective function with the goal of minimizing total transportation cost, total transportation time, total carbon emissions, and total transport volume fluctuations.

[0088] The objective optimization function is a mathematical expression whose output value represents the comprehensive performance evaluation of the coal transportation network. The optimal transportation scheme is sought by minimizing this function value. The function can be a multi-objective function, which can be expressed as a weighted sum or integrate the four sub-objectives of total transportation cost, total transportation time, total carbon emissions, and total transport volume fluctuation using other multi-objective optimization methods.

[0089] In this embodiment, the terminal integrates the four indicators determined in the previous step—total transportation cost, total transportation time, total carbon emissions, and total transport volume fluctuation—into a single objective optimization function using mathematical modeling. Each sub-objective can be assigned a weight coefficient to construct a weighted sum-form single-objective function, for example: Objective optimization function = w1 * total transportation cost + w2 * total transportation time + w3 * total carbon emissions + w4 * total transport volume fluctuation, where the weight coefficients reflect the relative importance of each sub-objective in the optimization. The terminal can determine the weight coefficients based on preset optimization strategies or management needs to ensure that the function accurately reflects the comprehensive optimization requirements for cost, time, environmental protection, and stability. The function construction must ensure that the dimensions of each sub-objective are uniform or standardized to guarantee the rationality and comparability of the calculation. Specifically, the objective function can be constructed as follows:

[0090]

[0091] Where C represents total transportation cost, T represents total transportation time, E represents total carbon emissions, and F represents total volume fluctuation.

[0092] Step 306: Determine the constraints of the objective optimization function based on the coal transportation network topology, node parameters, and transportation parameters.

[0093] Constraints can be restrictions or requirements that must be met during the optimization process. They specify the range of possible solutions and ensure the feasibility of the optimization scheme in a real network. Constraints are usually expressed as equality or inequality and are set based on the network's physical structure and operational rules.

[0094] In this embodiment, the terminal analyzes the structural characteristics of the coal transportation network topology and, in conjunction with specific node parameters (such as node capacity and processing capacity) and transportation parameters (such as transportation edge capacity and transportation mode availability), identifies and formally describes all the physical and operational constraints that must be followed. Common constraints include: node flow balance constraints (i.e., the total amount of coal entering a node equals the total amount of coal leaving a node, except for supply and demand nodes), node processing capacity constraints (the amount of coal processed by a node does not exceed its maximum throughput), transportation edge capacity constraints (the amount of coal passing through a transportation edge does not exceed its maximum transportation capacity), transportation mode selection constraints (a specific transportation edge only supports a specific transportation mode), and coal type supply and demand constraints (the supply and demand of each type of coal are equal). The terminal expresses these constraints mathematically, forming a set of equations or inequalities.

[0095] Specifically, constraints may include:

[0096] A directed transport edge can only use one transport mode for coal at a time, as shown in the following formula:

[0097]

[0098] in, The variables are 0 and 1, and the coal is transported between node i and node j using the transportation method m. a A value of 1 indicates a transportation operation is being performed; otherwise, a value of 0 indicates a transportation operation is being performed. M represents the set of transportation modes (railway, road, and shipping). L represents the set of transportation edges between transportation nodes (including railway edges, road edges, and shipping edges).

[0099] When coal is transferred at node j, it will be transferred at most once, meaning the mode of coal transportation will change at most once, as shown in the following formula:

[0100]

[0101] in, The variables are 0 and 1, and the coal at node j is determined by the transportation method m. a Convert to transportation mode m b If the value is 1, then the value is 1; otherwise, it is 0. G represents the set of transit nodes in the transportation network.

[0102] The type and quantity of coal transported from a production node shall not exceed its production capacity, as shown in the following formula:

[0103]

[0104] in, This represents the annual transport volume of k types of coal on a directed transport edge (i, j), in tons per year. A directed transport edge (i, j) means that coal can only be transported from node i to node j on that transport edge. kThis represents the annual production capacity of a production node for k types of coal, expressed in tons per year. S represents the set of production nodes in the transportation network, and K represents the set of coal types.

[0105] The type and quantity of coal transported to the demand nodes must meet the demand of the demand nodes, as shown in the following formula:

[0106]

[0107] Among them, D k This represents the annual demand of demand nodes for type k coal, expressed in tons per year. D represents the set of demand nodes in the transportation network.

[0108] A directed transport edge using the m-th a The amount of coal transported by any mode of transport shall not exceed its maximum transport capacity, as shown in the following formula:

[0109]

[0110] in, Indicates coal at the mth order. a The maximum transport volume from node i to node j using a particular transport mode, expressed in tons (t).

[0111] At transfer node j, the mth a Transformation of one mode of transportation into the mth mode b The amount of coal transported by any mode of transport shall not exceed its maximum transshipment capacity, as shown in the following formula:

[0112]

[0113] in, This indicates that coal at node j is generated by the m-th node. a Transformation of one mode of transportation into the mth mode b The maximum transshipment capacity for a particular mode of transport, expressed in tons (t).

[0114] To ensure that the transportation mode change that occurs at a node corresponds to the transportation mode of the edges before and after the node, as shown in the following formula:

[0115]

[0116] in, The variables are 0 and 1, and the coal is transported between node j and node h using the transportation method m. a A value of 1 indicates that a transportation operation is being performed; otherwise, a value of 0 indicates that a transportation operation is being performed. V represents the set of all nodes in the transportation network.

[0117] The transit node must comply with the flow balance constraint, that is, the total amount of coal transported to the node is equal to the total amount of coal transported out of the node, as shown in the following formula:

[0118]

[0119] Step 308: Obtain the objective optimization model based on the constraint conditions constraining the objective optimization function.

[0120] In this embodiment, the terminal integrates the constructed objective optimization function with all determined constraints to form a structurally complete mathematical optimization model. The model is typically expressed as follows: under the premise of satisfying all constraints, solve for decision variables (such as the choice of transportation mode and the allocation of coal transportation volume on each transportation route) to minimize the objective optimization function.

[0121] By quantifying total transportation costs, time, carbon emissions, and volume fluctuations, a comprehensive and multi-dimensional optimization index system is established. This enables the model to simultaneously consider economic, efficiency, environmental, and stability optimization, improving the comprehensiveness of the final transportation strategy. Furthermore, rigorous constraints are set to ensure that the final transportation strategy conforms to actual production and transportation conditions.

[0122] In an exemplary embodiment, at least some of the nodes among the plurality of nodes are transit nodes; the node parameters of each transit node include transit information and unit transit cost, where the unit transit cost is the unit cost of converting coal between different transportation modes corresponding to the transit node; the transportation parameters of each transportation edge include transportation information, total transport volume, unit freight rate, transportation distance, interruption probability, and interruption cost, where the total transport volume is the total transport volume of different types of coal corresponding to the transportation edge, the unit freight rate is the unit freight rate of different transportation modes corresponding to the transportation edge, the transportation distance is the transportation distance of different transportation modes corresponding to the transportation edge, and the interruption probability and interruption cost are the probability and cost of transportation interruption corresponding to each transportation edge; for example Figure 4 As shown, step 302 above includes steps 402 to 408, wherein:

[0123] Step 402: Based on the total transport volume, unit freight rate, transport distance, and transport information, determine the transport costs of different types of coal transported by different transport methods for each transport edge.

[0124] Transportation costs can be the direct expenses incurred in transporting a certain type of coal along a transportation edge using a certain transportation method. Their value is determined by the total volume of that type of coal transported along that transportation edge, the unit freight rate of that transportation method (the cost per ton-kilometer or per ton), the transportation distance of that method along that transportation edge, and transportation information (the set of transportation methods allowed or permitted by that transportation edge).

[0125] In this embodiment, the terminal obtains the transportation parameters for each transportation edge in the coal transportation network topology graph. These parameters include the total transportation volume of various types of coal on that edge, the unit freight rate and transportation distance for different transportation modes (such as railway, highway, and waterway), and transportation information indicating the availability of transportation modes. For each type of coal and each available transportation mode on each transportation edge, the terminal multiplies the corresponding total transportation volume, unit freight rate, and transportation distance to calculate the cost of transporting that type of coal on that edge using that transportation mode. Then, the calculation results for all transportation modes and coal types are summarized to obtain the total transportation cost for that transportation edge. This process traverses all transportation edges to ensure that the transportation cost of each path segment in the network is accurately quantified.

[0126] Step 404: Based on the total transport volume, unit transshipment cost, and transshipment information, determine the transshipment cost for different types of coal at each transshipment node to be converted between different modes of transport.

[0127] The transshipment cost for different types of coal at a transshipment node, which involves switching between different modes of transport, can be considered as the additional operational cost incurred when coal passes through a transshipment node during transportation, changing from one mode of transport to another (e.g., from rail to waterway). Its value is determined by the total volume of various types of coal passing through the node, the unit transshipment cost (usually the cost per ton) corresponding to the specific mode of transport conversion, and the transshipment information (the mode of transport conversion relationships supported by the transshipment node).

[0128] In this embodiment, the terminal identifies all transit nodes in the coal transportation network topology and obtains their node parameters, including transit information (such as the possibility of transferring from rail to waterway) and the unit transit cost corresponding to different combinations of transportation modes. For each transit node, the terminal calculates the transit cost generated by completing the mode conversion at that node by multiplying the corresponding total volume of various types of coal passing through the node, based on the total volume of various types of coal inferred from the actual transportation route planning and the specific transportation mode conversion type that occurs at that node. This process requires traversing all transit nodes and all possible transportation mode conversion scenarios for various types of coal, and summarizing the results.

[0129] Step 406: Determine the total interruption cost for each transport edge based on the interruption probability and the interruption cost.

[0130] The total interruption cost for each transport edge can be defined as the expected economic loss incurred in response to or to compensate for the interruption, taking into account the risk of interruption due to unforeseen events (such as equipment failure or weather conditions). Its value is determined by the interruption probability (i.e., the likelihood of an interruption) and the interruption cost (i.e., the additional costs incurred once an interruption occurs, such as delay losses or detour costs).

[0131] In this embodiment, for each transport edge, the terminal extracts two risk indicators from its transport parameters: interruption probability and interruption cost. The terminal multiplies the interruption probability of each transport edge by its interruption cost to calculate the expected interruption cost (i.e., the total interruption cost) of that transport edge. After calculation, the total interruption cost of each transport edge can be treated as an independent cost factor to be aggregated.

[0132] Step 408: Determine the total transportation cost based on transportation costs, transshipment costs, and total interruption costs.

[0133] The total transportation cost can be the sum of all economic costs incurred by coal in the entire transportation network from origin to destination.

[0134] In this embodiment, the terminal sums up the previously calculated transportation costs of all transportation edges involving coal transportation, the transshipment costs of all transshipment nodes involving coal transshipment, and the total interruption costs of all transportation edges involving coal transportation. This summation process requires no duplicate calculations or omissions; that is, the three types of costs must cover all relevant transportation edges and nodes and must not overlap. The summed value is the overall transportation cost of the entire coal transportation network, which is a macroeconomic indicator that integrates direct transportation costs, node operation costs, and expected risk costs.

[0135] Specifically, the formula for calculating the total transportation cost is as follows:

[0136]

[0137] Where C1 represents transportation cost, C2 represents transit cost, and C3 represents total interruption cost. Indicates coal at the mth order. a The unit freight rate for transporting goods from node i to node j using this mode of transport is expressed in yuan / (ton·km). Indicates coal at the mth order. a The transportation distance from node i to node j for each mode of transport is expressed in km (kilometers). This indicates that coal at node j is generated by the m-th node. a Transformation of one mode of transportation into the mth mode b The unit transshipment cost for each mode of transportation, expressed in yuan / t (ton), where P(i,j) represents the probability of interruption of the directed transport edge (i,j) between transport nodes. This represents the penalty cost when the directed transport edge (i,j) is interrupted, in yuan.

[0138] In reality, coal transportation networks are complex and dynamic systems. Factors such as weather changes, traffic congestion, equipment failures, and policy adjustments can all lead to transportation route disruptions. If only a static network assumption is made, assuming that transportation routes and node capabilities are fixed, it will be difficult to reflect the dynamic changes within the coal transportation network. This embodiment considers transportation disruptions caused by weather, traffic, and equipment failures at each participating transportation edge, quantifying the impact of dynamic changes on transportation routes and improving the stability and reliability of coal transportation planning.

[0139] In an exemplary embodiment, the transportation parameters further include transportation process time, which is the time taken for different modes of transportation to travel along the transportation edge; the node parameters further include transfer time, which is the time taken for different modes of transportation to switch between different modes of transportation at a transfer node; such as Figure 5 As shown, step 302 above includes steps 502 to 506, wherein:

[0140] Step 502: Determine the total transportation process time for each transportation edge based on the transportation process time and transportation information.

[0141] The total transportation process time of a transportation edge can be defined as the transit time of coal at a given transportation edge using a specific transportation method. Its value depends on the transportation process time of that transportation edge (i.e., the transportation time for different transportation methods on that edge) and the transportation information (i.e., the transportation methods permitted or actually used on that edge). For a specific type of coal and a selected transportation method, the transportation process time on that edge can be directly obtained from the transportation parameters.

[0142] In this embodiment, the terminal obtains the transportation parameters for each transportation edge in the coal transportation network topology graph, including transportation process time (the time for different transportation modes to transport on that edge, e.g., 10 hours for rail transport and 15 hours for waterway transport) and transportation information (identifying the set of transportation modes available for that edge). For each transportation edge, based on the planned or calculated transportation mode selection results for various types of coal, the corresponding transportation process time is selected, and the transportation process times for all types of coal passing through that edge are accumulated to obtain the total transportation process time for that edge. This calculation must be based on the allocation scheme of transportation paths and transportation modes to ensure that the time calculation is consistent with the actual transportation plan.

[0143] Step 504: Based on the total transport volume, transit time, and transit information, determine the total transit time for different types of coal to be transferred between different modes of transport at each transit node.

[0144] The total transit time at a transit node can be defined as the sum of additional operations and waiting times incurred when coal passes through a transit node during transportation due to the conversion between different modes of transport (such as unloading from a rail and reloading onto a ship). This value is determined by the total volume of various types of coal passing through the node, the transit time required for specific mode-of-transport conversions (usually referring to the processing time per ton of coal), and transit information (identifying the mode-of-transport conversion relationships supported by the node).

[0145] In this embodiment, the terminal identifies each transfer node in the coal transportation network and obtains its node parameters, including transfer information (such as support for railway-to-waterway conversion) and the unit transfer time corresponding to different combinations of transportation modes (e.g., 0.1 hours per ton of coal transferred from railway to waterway). For each transfer node, based on the total volume of various types of coal actually flowing through that node in the transportation plan and the specific transportation mode conversion type occurring at that node, the corresponding total volume is multiplied by the unit transfer time to calculate the total transfer time caused by the mode conversion at that node. This process needs to cover all transfer nodes and all possible transportation mode conversion scenarios.

[0146] Step 506: Determine the total transportation time based on the total transportation process time and the total transfer time.

[0147] The total transportation time can be the sum of all the time spent transporting coal from the starting point to the destination and completing the entire flow process in the network.

[0148] In this embodiment, the terminal sums the total transportation time of all participating transportation edges with the total transit time of all participating transit nodes. This summation process must ensure no duplicate calculations or omissions, meaning that the two time components cover all relevant transportation edges and nodes and do not overlap. The summed value is the overall transportation time of the entire coal transportation network, which is a macro-efficiency indicator that integrates the time spent on line movement and the time spent on node operation.

[0149] Specifically, the formula for calculating the total transportation time is as follows:

[0150]

[0151] Where T1 represents the total transportation process time, and T2 represents the total transfer time. Indicates coal at the mth order. a The transportation time from node i to node j for each transportation mode is expressed in hours (h). This indicates that coal at node j is generated by the m-th node. a Transformation of one mode of transportation into the mth mode b The unit transit time for each mode of transportation, expressed in hours (h / t).

[0152] By breaking down the total transport time into transit time and transfer time, the time calculation is expanded from a single transit time to include the operational time of multimodal transport nodes, thus improving the completeness and accuracy of the time model. Furthermore, introducing a transfer time parameter quantifies the time delay caused by mode of transport switching, enabling the optimization model to more accurately assess the overall efficiency of different intermodal transport schemes, thereby supporting the generation of more reasonable route and mode combinations.

[0153] In an exemplary embodiment, the transportation parameters further include a first unit carbon emission, which is the unit carbon emission when different modes of transportation are transported at the transportation edge; the node parameters further include a second unit carbon emission, which is the unit carbon emission during the conversion between different modes of transportation at the transit node; such as Figure 6 As shown, step 302 above includes steps 602 to 606, wherein:

[0154] Step 602: Based on the total transport volume, the carbon emissions of each first unit, the transport distance, and the transport information, determine the transport carbon emissions of different types of coal transported by different transport methods along each transport edge.

[0155] The carbon emissions from transporting different types of coal along a transport edge using different transport methods can be defined as: the direct or indirect greenhouse gas emissions generated by coal transported along a certain transport edge using a specific transport method. This value is determined by the total volume of all types of coal transported through that edge, the first unit carbon emission of that transport method along that edge (usually referring to the CO2 equivalent emitted per ton-kilometer), the transport distance of that transport method, and transport information (identifying the set of permitted transport methods along that edge).

[0156] In this embodiment, the terminal obtains the transportation parameters for each transportation edge in the coal transportation network topology graph, including the total transportation volume of various types of coal, the first unit carbon emission corresponding to different transportation modes, the transportation distance, and transportation information. For each type of coal and each available transportation mode on each transportation edge, the terminal multiplies the corresponding total transportation volume, the first unit carbon emission, and the transportation distance to calculate the carbon emission generated by transporting that type of coal on that edge using that transportation mode. Then, the calculation results for all transportation modes and coal types are summarized to obtain the total transportation carbon emission of that transportation edge. This process traverses all transportation edges to ensure that the carbon emission of each path segment in the network is accurately quantified.

[0157] Step 604: Based on the total transport volume, the carbon emissions of each second unit, and the transshipment information, determine the transshipment carbon emissions of different types of coal converted between different modes of transport at each transshipment node.

[0158] The carbon emissions from the transfer of different types of coal between different modes of transport at a transshipment node can be categorized as follows: The direct or indirect greenhouse gas emissions generated when coal passes through a transshipment node during transport due to transfer operations (such as loading / unloading, temporary storage, and transshipment) between different modes of transport. This value is determined by the total volume of various types of coal flowing through the node, the second unit carbon emission corresponding to a specific mode of transport transfer (usually referring to the carbon dioxide equivalent generated per ton of coal transfer operation), and transshipment information (identifying the mode of transport transfer relationships supported by the node).

[0159] In this embodiment, the terminal identifies each transit node in the network and obtains its node parameters, including transit information and the second unit carbon emission corresponding to different combinations of transportation mode conversions. For each transit node, based on the total volume of various types of coal actually flowing through that node in the transportation plan and the specific transportation mode conversion type that occurs at that node, the corresponding total volume is multiplied by the second unit carbon emission to calculate the transit carbon emission generated by the mode conversion at that node. This process needs to cover all transit nodes and all possible transportation mode conversion scenarios, and the results are summarized.

[0160] Step 606: Determine the total carbon emissions based on the carbon emissions from transportation and transit.

[0161] Total carbon emissions can be the sum of greenhouse gas emissions generated by coal throughout the entire transportation network, from the origin to the destination.

[0162] In this embodiment, the terminal sums the total carbon emissions from all transport edges with the total carbon emissions from all transit nodes. This summation process requires no duplicate calculations or omissions; that is, the two carbon emission figures must cover all relevant transport edges and nodes and must not overlap. The summed value represents the overall carbon emissions of the entire coal transport network, which is a macro-level measure for comprehensively assessing the environmental impact of transport activities.

[0163] Specifically, the formula for calculating total carbon emissions is as follows:

[0164]

[0165] E1 represents carbon emissions from transportation, and E2 represents carbon emissions from transshipment. This represents the unit carbon emission of coal transported from node i to node j using the ma-th transportation method, expressed in kg (kilograms) / (t·km). This represents the unit carbon emission of coal at node j when it is switched from the ma-th transportation mode to the mb-th transportation mode, expressed in kg / t.

[0166] By breaking down total carbon emissions into transportation carbon emissions and transit carbon emissions, environmental assessments are expanded from single in-transit emissions to include emissions from node operations, significantly improving the completeness and systematic nature of carbon emission accounting and conforming to the concept of life cycle analysis.

[0167] In an exemplary embodiment, the transportation parameters also include historical average transportation volume and actual annual transportation volume, where historical average transportation volume is the historical average annual transportation volume of coal at the transportation edge, and actual annual transportation volume is the actual annual transportation volume of different types of coal at the transportation edge; step 302 above includes: determining the absolute value difference between each historical average transportation volume and each actual annual transportation volume, and determining the total transportation volume fluctuation.

[0168] The absolute difference between the historical average transport volume and the actual annual transport volume can be defined as the absolute value of the difference between the actual annual transport volume of each type of coal and the historical average annual transport volume of the corresponding coal for each transport edge. The total transport volume fluctuation can be the sum or weighted sum of the absolute differences of each type of coal calculated across all transport edges in the entire coal transport network, used to quantify the degree of deviation of the overall network transport volume from the historical average level.

[0169] In this embodiment, the terminal obtains the historical annual average transport volume (representing the long-term, stable average level of coal transport volume for that edge) and the actual annual transport volume of each type of coal (representing the specific transport volume within the current or planning period) from the transport parameters of each transport edge in the coal transport network topology. For each transport edge, the terminal calculates the absolute value of the difference between the actual annual transport volume and the historical average transport volume for each type of coal. Subsequently, the terminal sums all the absolute value differences calculated for all transport edges in the network, or performs a weighted summation based on the transport importance of each edge, ultimately obtaining a single numerical indicator characterizing the stability of the entire network's transport volume, namely, the total transport volume fluctuation.

[0170] Specifically, the formula for calculating the fluctuation of total freight volume is as follows:

[0171]

[0172] Among them, h （i,j） This represents the historical average volume of coal transported along the directed transport edge (i,j), in tons per year.

[0173] By calculating the fluctuations in total transport volume, the balance and stability requirements of coal flow in the transportation network are reflected. This allows the optimization process to not only focus on absolute performance indicators such as cost, time, and carbon emissions, but also to take operational stability and the degree of closeness to historical norms as optimization dimensions. This helps to generate transportation solutions that are easier to actually schedule and manage, and avoid large fluctuations.

[0174] In one exemplary embodiment, such as Figure 7As shown, step 208 above includes steps 702 and 704, wherein:

[0175] Step 702: Using transportation routes, transportation methods, and the transportation volume of various types of coal as decision variables, solve the objective optimization model to obtain multiple solutions and corresponding transportation strategies and objective function values.

[0176] In this context, decision variables can be unknown quantities in the mathematical model whose values ​​need to be determined through the solution process. Specifically, in this step, they refer to the transportation routes to be determined (i.e., the sequence of nodes and transportation edges from the starting point to the destination), the transportation modes used on each route (such as railways, highways, and waterways), and the transportation volume of various types of coal (such as thermal coal and coking coal) on each route. A transportation strategy refers to a complete transportation plan composed of a set of specific decision variable values. The objective function value is the numerical value calculated by substituting a specific transportation strategy into the objective optimization function. This value comprehensively reflects the strategy's performance across multiple dimensions, including total transportation cost, total transportation time, total carbon emissions, and fluctuations in total transport volume.

[0177] In this embodiment, the terminal uses a preset optimization algorithm to solve the constructed target optimization model. During the solution process, the terminal sets the selection of transportation routes (i.e., which edges in the network are used), the transportation methods used on each used edge, and the specific transportation quantities of various types of coal on these edges as decision variables in the model. By running the optimization algorithm, the terminal searches the feasible space of the decision variables, ultimately obtaining one or more combinations of decision variable values ​​that bring the target optimization function to or near its optimum. Each such combination constitutes a specific transportation strategy, and the terminal calculates the objective function value corresponding to each strategy. The solution process must ensure that all solutions satisfy all constraints of the model.

[0178] Step 704: Determine the transportation route, the corresponding transportation mode, and the transportation volume of various types of coal among multiple transportation strategies based on the objective function value.

[0179] In this embodiment, after obtaining multiple transportation strategies and their objective function values, the terminal evaluates and compares these strategies according to preset decision rules. If the objective optimization model is a single-objective weighted sum form, the strategy with the smallest objective function value is usually selected as the optimal solution. If the solution process generates a set of undominated solutions (Pareto front), the terminal may select a final solution from the set of undominated solutions based on additionally set multi-objective decision rules (such as specific priorities or decision-maker preferences). Finally, the terminal analyzes and outputs the specific decision variable values ​​implied by the selected solution to form a clear transportation instruction, namely, a detailed transportation route, the transportation mode for each segment of the route, and the specific transportation volume of various types of coal on different segments.

[0180] Specifically, such as Figure 8 As shown, when solving the objective optimization model, the NSGA-III can be used to solve the transportation route scheme. The specific steps include:

[0181] 1. Initialize parameters:

[0182] (1) Set the population size N=400, the crossover probability Pc=0.9, the mutation probability Pm=0.0025, and the maximum number of iterations gen=300.

[0183] (2) Initialize the population: Randomly generate N feasible solutions as the initial population, each solution containing all decision variables: (Determine the coal transportation volume of type k coal). (Select transportation method) (Select transit combination).

[0184] (3) Chromosome coding: A segmented and hierarchical coding strategy is adopted.

[0185] Coal transport allocation uses real-number encoding: transport volume is allocated to each transport edge (i,j) and coal type k. This represents the transport volume of a certain type of coal along this edge. Subsequent crossover and mutation operations only crossover the transport volume of the same type of coal, and mutations are performed independently for each coal type.

[0186] The transportation method uses binary encoding: for each transportation edge Assign a mode of transportation M = {road (diesel), road (electric), railway, shipping}, where 1 represents the mode of transportation and 0 represents the mode of transportation not used.

[0187] The transit decision uses binary encoding: for each transit node Possible mode of transport transitions (road → rail, rail → road, rail → waterway, waterway → road, waterway → rail) are assigned 0 / 1. At a certain transfer node, a transition between two modes of transport is assigned 1, and no transition is assigned 0.

[0188] In summary, the encoding of a transportation edge (i,j) includes three layers: the coal transportation volume decision layer (determines the transportation volume of different types of coal on a transportation edge), the transportation mode decision layer (determines the transportation mode of a transportation edge), and the transit decision layer (determines the transit combination of node j).

[0189] 2. Non-dominated sorting:

[0190] (1) Calculate the target values: For each individual in the initial population, calculate the corresponding four target function values: transportation cost, transportation time, carbon emissions, and transportation volume fluctuation.

[0191] (2) Fast non-dominated sorting: Domination relation definition: If all objective values ​​of solution A are better than or equal to solution B, and at least one objective value is strictly better than B, then A dominates B.

[0192] Calculate the dominance count (how many solutions dominate it) and dominance set (how many solutions it dominates) for each solution. Assign non-dominated solutions (dominance count = 0) to Front1. Update the dominance count for the remaining solutions. Find new non-dominated solutions and assign them to Front2. Repeat the above process until all solutions are classified.

[0193] 3. Generate reference points: Determine the target space dimension as 4 (transportation cost, transportation time, carbon emissions, and volume fluctuations), divide the layers into 6 layers, and generate 84 reference points. Use the Das and Dennis systematic methods to generate uniformly distributed reference points, and divide the target space uniformly along each target axis to generate a structured reference point set.

[0194] 4. Individual association with reference point:

[0195] (1) Target value normalization: The four targets of transportation cost, transportation time, carbon emissions, and transportation volume fluctuation for each individual in the population are normalized to eliminate the difference in dimensions. The normalization method is as follows (taking transportation cost as an example):

[0196]

[0197] Where c is the transportation cost for each individual in the population, c min To minimize transportation costs within the population, c max This represents the highest transportation cost within the population.

[0198] (2) Calculate the vertical distance: Construct a straight line from the origin to the reference point, calculate the projection point of each individual in the population in the normalized target space, and calculate the vertical distance of the individual to the reference line.

[0199] (3) Associating individuals with reference points: Associating each individual with the nearest reference point and counting the number of individuals associated with each reference point.

[0200] 5. Niche conservation strategy:

[0201] (1) Select individuals to join the new population in order of Front level: Prioritize all individuals in Front 1. If the number of individuals in Front 1 is greater than N, then filter the individuals in Front 1 according to the screening rules in (2). If the number of individuals in Front 1 is less than N, then continue to select individuals in Front 2. Repeat the above steps until the total number of selected individuals fills the population size N.

[0202] (2) Filter the last front: prioritize the solution corresponding to the reference point with fewer associated individuals. When the same reference point is associated with multiple solutions, select the one that is closer, until the population size N is filled.

[0203] 6. Genetic manipulation:

[0204] (1) Simulated binary crossover: Randomly select two individuals from the parents, and assign crossover probability P to each decision variable. c Crossover is performed with a value of 0.9, and offspring are generated using the SBX operator.

[0205] (2) Polynomial variation: For each decision variable in the offspring, according to probability P m =0.0025 is used to mutate, and a perturbation is introduced using a polynomial mutation operator.

[0206] (3) Constraint repair: Check whether the offspring individuals satisfy all constraints, and adjust the solutions that do not satisfy the constraints: adjust the transportation volume to not exceed the maximum transportation capacity, ensure that each edge selects only one transportation mode, limit the number of transfers, etc.

[0207] 7. Termination and Output:

[0208] Check if the maximum number of iterations gen=300 has been reached, and check if the Pareto front has converged (no significant improvement for several consecutive generations). If either condition is met, terminate; otherwise, return to step 2.

[0209] The final output is the Pareto optimal frontier: non-dominated solutions are extracted from the final population, the solution set is post-processed (removing duplicate solutions), and the transportation scheme and objective function value corresponding to each solution are output.

[0210] By comparing and deciding on multiple options based on the objective function value, it is ensured that the final selected transportation route, transportation mode and coal transportation volume allocation plan achieves the best or most satisfactory balance in multiple objectives such as cost, time, carbon emissions and stability under the premise of meeting all practical constraints, which significantly improves the scientific and systematic nature of transportation decision-making.

[0211] 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.

[0212] Based on the same inventive concept, this application also provides a multimodal transport planning device for implementing the multimodal transport planning method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more multimodal transport planning device embodiments provided below can be found in the limitations of the multimodal transport planning method described above, and will not be repeated here.

[0213] In one exemplary embodiment, such as Figure 9 As shown, a multimodal transport planning device is provided, comprising:

[0214] Topology module 901 is used to construct a coal transportation network topology graph based on the nodes and transportation edges in the coal transportation network; there are multiple nodes and multiple transportation edges, and the transportation edges are the transportation paths between nodes.

[0215] The data acquisition module 902 is used to acquire the node parameters of the nodes and the transportation parameters of the transportation edges in the coal transportation network.

[0216] Modeling module 903 is used to construct a target optimization model based on the coal transportation network topology, node parameters, transportation parameters, and preset optimization objectives.

[0217] The solver module 904 is used to determine the transportation route and the corresponding transportation mode and the transportation volume of various types of coal based on the objective optimization model.

[0218] In one embodiment, the modeling module 903 is further configured to determine the total transportation cost, total transportation time, total carbon emissions, and total volume fluctuation of various types of coal transportation based on the coal transportation network topology, node parameters, and transportation parameters; construct an objective optimization function with the goal of minimizing the total transportation cost, total transportation time, total carbon emissions, and total volume fluctuation; determine the constraints of the objective optimization function based on the coal transportation network topology, node parameters, and transportation parameters; and obtain the objective optimization model based on the constraints of the objective optimization function.

[0219] In one embodiment, at least some of the nodes among the plurality of nodes are transit nodes; the node parameters of each transit node include transit information and unit transit cost, where the unit transit cost is the unit cost of converting coal between different modes of transportation corresponding to the transit node; the transportation parameters of each transportation edge include transportation information, total transport volume, unit freight rate, transportation distance, interruption probability, and interruption cost, where the total transport volume is the total transport volume of different types of coal corresponding to the transportation edge, the unit freight rate is the unit freight rate of different modes of transportation corresponding to the transportation edge, the transportation distance is the transportation distance of different modes of transportation corresponding to the transportation edge, and the interruption probability and interruption cost are... Interruption cost is the probability and cost of transportation interruption corresponding to each transportation edge; modeling module 903 is also used to determine the transportation cost of different types of coal transported by different transportation modes for each transportation edge based on the total transportation volume, unit freight rate, transportation distance and transportation information; to determine the transshipment cost of different types of coal switching between different transportation modes for each transshipment node based on the total transportation volume, unit transshipment cost and transshipment information; to determine the total interruption cost of each transportation edge based on the interruption probability and interruption cost; and to determine the total transportation cost based on the transportation cost, transshipment cost and total interruption cost.

[0220] In one embodiment, the transportation parameters also include transportation process time, which is the time for different transportation modes to transport along the transportation edge; the node parameters also include transfer time, which is the time for switching between different transportation modes in the transfer node; the modeling module 903 is also used to determine the total transportation process time of each transportation edge based on each transportation process time and each transportation information; to determine the total transfer time for switching between different types of coal in different transportation modes in each transfer node based on each total transport volume, each transfer time and each transfer information; and to determine the total transportation time based on the total transportation process time and the total transfer time.

[0221] In one embodiment, the transportation parameters further include a first unit carbon emission, which is the unit carbon emission when different transportation modes are transported at the transportation edge; the node parameters further include a second unit carbon emission, which is the unit carbon emission when different transportation modes are switched at the transit node; the modeling module 903 is also used to determine the transportation carbon emission of different types of coal transported at each transportation edge using different transportation modes based on each total transportation volume, each first unit carbon emission, each transportation distance, and each transportation information; to determine the transit carbon emission when different types of coal are switched between different transportation modes at each transit node based on each total transportation volume, each second unit carbon emission, and each transit information; and to determine the total carbon emission based on the transportation carbon emission and the transit carbon emission.

[0222] In one embodiment, the transportation parameters also include historical average transportation volume and actual annual transportation volume. The historical average transportation volume is the historical average annual transportation volume of coal at the transportation edge, and the actual annual transportation volume is the actual annual transportation volume of different types of coal at the transportation edge. The modeling module 903 is also used to determine the absolute value difference between each historical average transportation volume and each actual annual transportation volume to determine the total transportation volume fluctuation.

[0223] In one embodiment, the solution module 904 is further configured to use the transportation route, transportation mode, and transportation volume of various types of coal as decision variables to solve the objective optimization model, thereby obtaining multiple solutions corresponding to transportation strategies and objective function values; and to determine the transportation route and the corresponding transportation mode and transportation volume of various types of coal among multiple transportation strategies based on the objective function values.

[0224] Each module in the aforementioned multimodal transport planning device 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, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0225] In one exemplary embodiment, a computer device is provided, the internal structure of which can be as shown in the figure. Figure 10As 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 operation of the operating system and computer programs stored in the non-volatile storage media. The database stores control data for the computer device. 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 multimodal transport planning method.

[0226] Those skilled in the art will understand that Figure 10 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.

[0227] 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 described in the multimodal transport planning method embodiment.

[0228] 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 described in the multimodal transport planning method embodiment.

[0229] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps described in the multimodal transport planning method embodiment.

[0230] 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, and when executed, it 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.

[0231] 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.

[0232] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent 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 multimodal transport planning method, characterized in that, The method includes: A coal transportation network topology graph is constructed based on the nodes and transportation edges in the coal transportation network; the number of nodes and transportation edges are both multiple, and the transportation edges are the transportation paths between the nodes. Obtain the node parameters of the nodes and the transportation parameters of the transportation edges in the coal transportation network; Based on the coal transportation network topology, the node parameters, the transportation parameters, and the preset optimization objectives, a target optimization model is constructed. Based on the target optimization model, the transportation routes, corresponding transportation methods, and the transportation volumes of various types of coal are determined.

2. The method according to claim 1, characterized in that, The step of constructing a target optimization model based on the coal transportation network topology, the node parameters, the transportation parameters, and the preset optimization objective includes: Based on the coal transportation network topology, the node parameters, and the transportation parameters, the total transportation cost, total transportation time, total carbon emissions, and total volume fluctuations for various types of coal transportation are determined. Construct an objective function with the goal of minimizing the total transportation cost, the total transportation time, the total carbon emissions, and the fluctuation of the total transportation volume; The constraints of the objective optimization function are determined based on the coal transportation network topology, the node parameters, and the transportation parameters. The objective optimization model is obtained by constraining the objective optimization function based on the aforementioned constraints.

3. The method according to claim 2, characterized in that, At least some of the nodes are transit nodes; the node parameters of each transit node include transit information and unit transit cost, wherein the unit transit cost is the unit cost of converting coal between different transportation modes corresponding to the transit node; the transportation parameters of each transportation edge include transportation information, total transport volume, unit freight rate, transportation distance, interruption probability and interruption cost, wherein the total transport volume is the total transport volume of different types of coal corresponding to the transportation edge, the unit freight rate is the unit freight rate of different transportation modes corresponding to the transportation edge, the transportation distance is the transportation distance of different transportation modes corresponding to the transportation edge, and the interruption probability and interruption cost are the probability and cost of transportation interruption corresponding to each transportation edge; The step of determining the total transportation cost based on the coal transportation network topology, the node parameters, and the transportation parameters includes: Based on the total transport volume, unit freight rate, transport distance, and transport information, determine the transport costs of different types of coal transported by different transport methods for each transport edge; Based on the total transport volume, the unit transshipment cost, and the transshipment information, determine the transshipment cost for different types of coal at each transshipment node to be converted between different modes of transport; The total interruption cost of each transport edge is determined based on the interruption probability and the interruption cost. The total transportation cost is determined based on the transportation cost, the transit cost, and the total interruption cost.

4. The method according to claim 3, characterized in that, The transportation parameters also include transportation process time, which is the time taken for different transportation modes to transport goods along the transportation edge; the node parameters also include transfer time, which is the time taken for different transportation modes to switch between different transportation modes at the transfer node; determining the total transportation time based on the coal transportation network topology, the node parameters, and the transportation parameters includes: The total transportation process time for each of the aforementioned transportation processes and the aforementioned transportation information is determined based on the total transportation process time for each of the aforementioned transportation edges. Based on the total transport volume, the transfer time, and the transfer information, determine the total transfer time for different types of coal to be transferred between different modes of transport at each transfer node; The total transportation time is determined based on the total transportation process time and the total transfer time.

5. The method according to claim 3, characterized in that, The transportation parameters also include a first unit carbon emission, which is the unit carbon emission when different modes of transportation are transported at the transportation edge; the node parameters also include a second unit carbon emission, which is the unit carbon emission when different modes of transportation are switched at the transit node. The determination of total carbon emissions based on the coal transportation network topology, the node parameters, and the transportation parameters includes: Based on the total transport volume, the first unit carbon emission, the transport distance, and the transport information, determine the transport carbon emission of different types of coal transported by different transport methods along each transport edge; Based on the total transport volume, the second unit carbon emission, and the transshipment information, determine the transshipment carbon emission of different types of coal switching between different modes of transport at each transshipment node; The total carbon emissions are determined based on the carbon emissions from transportation and the carbon emissions from transshipment.

6. The method according to claim 3, characterized in that, The transportation parameters also include historical average transportation volume and actual annual transportation volume. The historical average transportation volume is the historical average annual transportation volume of coal along the transportation route, and the actual annual transportation volume is the actual annual transportation volume of different types of coal along the transportation route. The step of determining the total transport volume fluctuation based on the coal transport network topology, the node parameters, and the transport parameters includes: Determine the absolute value difference between each of the historical average transport volumes and each of the actual annual transport volumes to determine the fluctuation of the total transport volume.

7. The method according to any one of claims 1 to 6, characterized in that, The determination of transportation routes and corresponding transportation modes and coal transportation volumes based on the target optimization model includes: By using transportation routes, transportation methods, and the transportation volume of various types of coal as decision variables, the objective optimization model is solved to obtain multiple solutions and corresponding transportation strategies and objective function values. Based on the objective function value, the transportation route, the corresponding transportation mode, and the transportation volume of each type of coal are determined among multiple transportation strategies.

8. A multimodal transport planning device, characterized in that, The device includes: The topology module is used to construct a coal transportation network topology graph based on the nodes and transportation edges in the coal transportation network; the number of nodes and transportation edges are both multiple, and the transportation edges are the transportation paths between the nodes. The data acquisition module is used to acquire the node parameters of the nodes and the transportation parameters of the transportation edges in the coal transportation network. The modeling module is used to construct a target optimization model based on the coal transportation network topology, the node parameters, the transportation parameters, and the preset optimization objectives. The solution module is used to determine the transportation route and the corresponding transportation mode and the transportation volume of various types of coal based on the target optimization model.

9. A computer device, characterized in that, It includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method according to any one of claims 1 to 7.

10. 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 7.

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