Transfer scheduling method, device and storage medium

Abstract

The embodiments of the present application provide a transshipment scheduling method, device, and storage medium, which relate to the technical field of road-rail transshipment scheduling. The method includes: generating a bid transport order, disclosing the bid transport order to different types of carriers participating in the bidding; determining a target carrier based on a historical price pricing strategy and a combined price pricing strategy; constructing an objective function based on the target carrier's pricing strategy quotation under a stable system state, and generating a transshipment scheduling plan for the target carrier's pricing strategy under a stable system state for one or more bid transport orders that the target carrier has won the bid based on the objective function. The method provided by the embodiments of the present application can reduce enterprise costs and improve road-rail transshipment efficiency and resource allocation efficiency.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of transfer scheduling technology, and in particular to a transfer scheduling method, device, and storage medium. Background Art

[0002] Currently, road-rail transshipment is a widely used intermodal transport mode. It combines the advantages of road transport—flexibility, convenience, short response time, and ample capacity—with the advantages of the rail transport network, including its extensive network coverage, high stability, and high speed, achieving continuous, integrated transportation. Containerized freight transport, a mode of transport that combines cargo in containers, offers advantages such as reduced costs, improved efficiency, and smoother road-rail transshipment. Containerized road-rail transshipment organically integrates road and rail freight transport, reducing unnecessary resource waste, reducing empty vehicle mileage, optimizing operational processes, and leveraging resources to maximize the benefits of intermodal transport. Within the road transport process, transportation service procurement is a critical and important step. This process involves transport companies obtaining transportation services from intermodal transport operators based on their actual operational conditions and transportation needs. This process directly impacts the efficiency of road-rail transshipment and the profitability of all stakeholders.

[0003] However, in the existing technology, this complex method of procuring road-rail transshipment transportation services and coordinating truck transportation routes has the following shortcomings:

[0004] 1. Transport carriers of different sizes and natures have different bidding behaviors due to their different number of employees, service areas and operating conditions. Existing transport service procurement ignores the heterogeneous behaviors and bidding strategies among competitors.

[0005] 2. The existing research on the road-rail transshipment of containers does not take into account the interactive behavior of market participants, and cannot consider the synergy between different transport orders under different pricing strategies, resulting in waste of transport capacity and reduced transport efficiency.

[0006] 3. In the transport organization of road-rail transfer, bid generation and route decision issues are ignored, making it difficult to determine fleet management and the allocation and route decisions of trucks within the entire time range, resulting in a lack of effective allocation of transport capacity.

[0007] Therefore, how to provide an optimization method for truck allocation and route decision-making that can take into account the bidding behavior and bidding strategies of highway carriers and meet the time window requirements of each node is an urgent problem that technicians in this field need to solve. Summary of the Invention

[0008] The embodiments of the present application provide a transfer scheduling method, device and storage medium, which can reduce enterprise costs and improve the efficiency of road-rail transfer and resource allocation efficiency.

[0009] In a first aspect, an embodiment of the present application provides a transshipment scheduling method, comprising:

[0010] Generating a bid transport order and disclosing the bid transport order to different types of carriers participating in the bidding; wherein the transport order includes a road-rail transshipment transport order and / or a rail-road transshipment transport order, and the bid transport order is generated based on the cargo owner's transport demand, which includes multiple information including the transport starting point, end point, cargo volume, start transport time requirement, and destination delivery time requirement; the different types of carriers include large transport enterprise carriers and small transport enterprise carriers;

[0011] Based on the historical price pricing strategy and the combined price pricing strategy, constructing a profit matrix for the different types of carriers participating in the bidding under the historical price pricing strategy and the combined price pricing strategy;

[0012] Solving the revenue matrix by replicating the dynamic model to obtain a pricing strategy under a system steady state, and determining a target carrier based on bids from different types of carriers participating in the bidding corresponding to the pricing strategy under the system steady state;

[0013] Based on the quotation of the target carrier's pricing strategy under the stable state of the system, an objective function is constructed with the goal of minimizing the total cost consisting of empty vehicle positioning cost, time value cost, transportation cost, warehousing cost and penalty cost and maximizing benefits. Based on the objective function, a transshipment scheduling plan of the target carrier's pricing strategy under the stable state of the system is generated for one or more bid transportation orders won by the target carrier.

[0014] In one possible implementation, the historical price pricing strategy includes a profit function:

[0015]

[0016] in,

[0017]

[0018] is the average unit cost of carrier a's bid for road-rail transshipment order g, ρ ag is the expected profit margin of carrier a's bid for road-rail transshipment order g, is the empty vehicle positioning cost of carrier a, is the probability that after the bidding road-rail transshipment transport order g arrives at the destination, its empty vehicle is repositioned and it wins another road-rail transshipment transport order, d vg is the average transportation distance of carrier a's bid for road-rail transshipment transport order g, N g The number of containers bidding for road-rail transshipment transport order g;

[0019] The combined price pricing strategy includes the profit function:

[0020]

[0021] in,

[0022]

[0023]

[0024]

[0025] is 0 or 1, is the unit bid price of the existing road-rail transshipment transport order j of carrier a, It is the empty vehicle positioning distance of carrier a from the end point of the existing road-rail transshipment transport order j to the starting point of the bidding road-rail transshipment transport order g.

[0026] In one possible implementation, solving the revenue matrix by replicating the dynamic model to obtain a pricing strategy in a system stable state, and determining a target carrier based on bids of different types of carriers participating in the bidding corresponding to the pricing strategy in the system stable state includes:

[0027] Determine the probability that the large-scale transport enterprise carrier and the small-scale transport enterprise carrier select different pricing strategies, and determine the average expected revenue value of the large-scale transport enterprise carrier and the small-scale transport enterprise carrier based on the probability of selecting different pricing strategies; wherein the average expected revenue value is calculated by the following formula:

[0028]

[0029] U SP is the average expected profit value of the small transport enterprise carrier, U LP is the average expected profit value of the large transport enterprise carrier, U SP1 is the expected profit value of the small transport enterprise carrier when adopting the historical price pricing strategy, U SP2 is the expected profit value of the small transport enterprise carrier when adopting the combined price pricing strategy, U LP1is the expected profit value of the large transport enterprise carrier when adopting the historical price pricing strategy, U LP2 The expected profit value of the large-scale transport enterprise carrier when adopting the combined price pricing strategy;

[0030] By solving the replication dynamic model, the asymptotic stability of the dynamic system is analyzed, and the stable state of each participant in the game is obtained; wherein the replication dynamic model is determined by the average expected revenue value of the large transportation enterprise carrier and the small transportation enterprise carrier; the replication dynamic model is represented by the following equation:

[0031]

[0032] Determine the optimal pricing strategy for the large transport enterprise carrier and the small transport enterprise carrier in a stable state, and select the carrier with the lowest quotation as the target carrier by comparing the quotations of the large transport enterprise carrier and the small transport enterprise carrier under the optimal pricing strategy.

[0033] In one possible implementation, the objective function is:

[0034]

[0035] Among them, i is the winning bid for the road-rail transshipment transport order, e is the winning bid for the rail-road transshipment transport order, and is the unit bid price of carrier a’s winning road-rail transshipment transport order i or winning rail-road transshipment transport order e, d vi and d ve is the average transportation distance of carrier a’s winning road-rail transshipment transport order i or winning rail-road transshipment transport order e, N i or N e is the number of containers of the winning bid for road-rail transshipment transport order i or the winning bid for road-rail transshipment transport order e, and are the unit transportation costs of the carrier’s winning road-rail transshipment transport order i or winning rail-road transshipment transport order e when route r is selected, and The transportation distance when the truck serving the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e chooses route r, C0 is the carrier's empty truck positioning cost, d ji and d je D is the empty truck travel distance from the destination of truck k with existing road-rail transshipment transport order j to the starting point of the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e, kjir and D kjeris the storage cost of the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e, f kjir and f kjer is the penalty cost for winning the bid for road-rail transshipment transport order i or winning the bid for rail-road transshipment transport order e, t a is the unit time value cost, n i The upper limit of the time window for the truck that wins the bid for the road-rail transshipment transport order i to pick up the goods from the customer, is the time when truck k arrives at the destination of the existing road-rail transport order j, q e The upper limit of the time window for the truck that wins the bid for the railway-road transshipment transport order e to go to the railway station to pick up the goods. and 0 or 1.

[0036] In one possible implementation, generating a transshipment scheduling solution for the target carrier's pricing strategy in the system stable state based on the objective function for one or more successful bid transportation orders of the target carrier includes:

[0037] If the target carrier wins a bid for a road-rail transshipment transport order or a bid for a rail-road transshipment transport order, the time when each vehicle's empty vehicle positioning ends is calculated based on the time it takes for the truck to complete serving the existing road-rail transshipment transport order and the distance of the empty vehicle positioning;

[0038] Sort the vehicles according to the end time of their empty vehicle positioning. i The winning road-rail transshipment transport order i of containers, from the Nth i Start with a vehicle that can complete empty vehicle positioning, assuming it is the latest vehicle to arrive during the vehicle matching process. If the latest arriving vehicle is vehicle k, then N vehicles that arrived earlier must be selected. i - 1 vehicle for container transportation;

[0039] Based on the latest empty vehicle positioning time of each vehicle, the empty vehicle positioning cost and time value cost are calculated; each time the transfer scheduling plan is called, the empty vehicle positioning cost and time value cost are directly sorted;

[0040] After selecting the vehicle that completes the empty vehicle positioning the latest, the vehicle matching process is completed; in the vehicle matching process, the N vehicles with the smallest sum of the empty vehicle positioning cost and the time value cost are selected. i - 1 vehicle;

[0041] After completing vehicle matching, route selection is performed. During the route selection process, given the latest empty vehicle positioning time, the route with the minimum total cost is traversed and selected.

[0042] After completing the vehicle matching and route selection process, the vehicle matching and route selection methods under the given latest positioning time and the time window requirements of each node are obtained. At the same time, the corresponding transportation cost, penalty cost, and warehousing cost can be calculated. The vehicle matching and route selection method corresponding to the minimum total cost is determined as the optimal vehicle scheduling method and route selection for the winning road-rail transshipment transport order.

[0043] In one possible implementation, generating a transshipment scheduling solution for the target carrier's pricing strategy in the system stable state based on the objective function for one or more successful bid transportation orders of the target carrier includes:

[0044] If the target carrier wins multiple bids for road-rail transshipment transport orders or multiple road-rail transshipment transport orders, dividing the solution of the multiple road-rail transshipment transport orders or the multiple road-rail transshipment transport orders into several stages according to the sequence characteristics of the multiple road-rail transshipment transport orders or the multiple road-rail transshipment transport orders;

[0045] For all the given winning road-rail transshipment transport orders i and winning rail-road transshipment transport orders e, let the solvers have N i , N e elements, and use N to sort the transport orders in the given order. i +N e bits represent the current solution state, where each state record corresponds to the vehicle dispatching method of the optimal solution;

[0046] The optimal solution for each state can be obtained by calling the transfer scheduling scheme of its adjacent states; among them, the states with a Hamming distance of 1 are adjacent states;

[0047] The optimal solution corresponding to the target state is determined through dynamic programming as the optimization algorithm result. The algorithm goal is to transfer from the initial state to the target state with the minimum cost.

[0048] In one possible implementation, the time when the empty vehicle positioning of each vehicle ends is calculated by the following formula:

[0049]

[0050] Among them, t ji and t je are the empty vehicle positioning time of the existing road-rail transshipment transport order j corresponding to the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e, The end time of truck k completing the existing road-rail transshipment transport order j, and The time when truck k, which has an existing road-rail transshipment transport order j, serves the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e and selects route r to arrange container transportation, is when the truck arrives at the starting point of the corresponding transshipment transport order. and They are the latest times that the truck arrives at the starting point of the corresponding transshipment transport order.

[0051] In one possible implementation, the number of vehicles allocated to serve the winning road-rail transshipment transport order i and the winning rail-road transshipment transport order e is determined by the following formula:

[0052]

[0053]

[0054]

[0055] Among them, the total number of trucks allocated from the existing road-rail transshipment transport orders is equal to the number of containers in the transport order. All allocated trucks can only serve one winning road-rail transshipment transport order or one winning rail-road transshipment transport order, and can only be used once.

[0056] In one possible implementation, during the path selection process, under the premise of a given latest empty vehicle location time, traversing the paths to select the path with the minimum total cost includes:

[0057] When the truck that wins the bid for road-rail transshipment transport order i arrives at the shipper later than the time window, the penalty cost is:

[0058]

[0059] When the truck that wins the bid for road-rail transshipment transport order i arrives at the railway station later than the time window, the storage cost incurred is:

[0060]

[0061] The weight of the container cannot exceed the capacity of the available train cars. If the container exceeds the train capacity, it must wait for the next train that can meet the train capacity requirements before it can depart. The resulting storage cost is expressed as:

[0062]

[0063] When the truck of the winning railway-highway transshipment transport order e arrives at the railway station later than the time window, the storage cost incurred is expressed as:

[0064]

[0065] When the truck that wins the bid for the railway-highway transshipment transport order e arrives at the shipper later than the time window, the penalty cost is expressed as:

[0066]

[0067] The goods are received based on the customer's time satisfaction, where the customer's time satisfaction can be expressed as:

[0068]

[0069]

[0070] Among them, f is the unit penalty cost, D kjir The storage cost of the winning road-rail transshipment transport order i at the railway station, is the time window of the railway station corresponding to the winning road-rail transshipment transport order i, The time when truck k, which has a road-rail transshipment transport order j, wins the bid for road-rail transshipment transport order i and chooses route r to arrive at the railway station, t s is the free storage time at the railway station, s t is the unit storage cost of the railway station, q i is the weight of the container that won the bid for road-rail transshipment transport order i, Q oi is the weight of other cargoes that the winning road-rail transshipment order i arrives at the railway station, Q i The train capacity of the railway station to which the winning road-rail transshipment transport order i is delivered, The time when truck k, which has an existing road-rail transshipment transport order j, wins the bid for the road-rail transshipment transport order e and chooses route r to reach the cargo owner, b e The upper limit of the delivery time window for the customer corresponding to the winning railway-highway transport order e, is customer satisfaction, h is the constraint value of customer satisfaction, The enterprise turnover inventory consumption period corresponding to the winning railway-highway transshipment transport order e; The best delivery time, It is the enterprise's safety stock consumption period.

[0071] In a second aspect, an embodiment of the present application provides a transport scheduling device, comprising:

[0072] An order generation module is configured to generate a bid transport order and disclose the bid transport order to different types of carriers participating in the bid; wherein the transport order includes a road-rail transshipment transport order and / or a rail-road transshipment transport order, and the bid transport order is generated based on the cargo owner's transport demand, which includes multiple information including the transport starting point, end point, freight volume, start transport time requirement, and destination delivery time requirement; the different types of carriers include large transport enterprise carriers and small transport enterprise carriers;

[0073] A construction module is used to construct a profit matrix of different types of carriers participating in the bidding under the historical price pricing strategy and the combined price pricing strategy based on the historical price pricing strategy and the combined price pricing strategy;

[0074] a determination module configured to solve the revenue matrix by replicating the dynamic model to obtain a pricing strategy under a system stable state, and determine a target carrier based on bids of different types of carriers participating in the bidding corresponding to the pricing strategy under the system stable state;

[0075] A solution generation module is used to construct an objective function with the objectives of minimizing the total cost consisting of empty vehicle positioning cost, time value cost, transportation cost, warehousing cost and penalty cost and maximizing benefits based on the quotation of the pricing strategy of the target carrier in the stable state of the system, and generate a transshipment scheduling solution of the pricing strategy of the target carrier in the stable state of the system based on the objective function for one or more bid transportation orders won by the target carrier.

[0076] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer-readable storage medium is run on a computer, the computer executes the method described in the first aspect.

[0077] In a fourth aspect, an embodiment of the present application provides a computer program, which, when executed by a computer, is used to execute the method described in the first aspect.

[0078] In one possible design, the program in the fourth aspect may be stored in whole or in part on a storage medium packaged with the processor, or may be stored in whole or in part on a memory not packaged with the processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] Figure 1 A flow chart of an embodiment of the transshipment scheduling method provided in this application;

[0080] Figure 2 A flow chart of another embodiment of the transshipment scheduling method provided by the present application;

[0081] Figure 3 A flow chart of another embodiment of the transshipment scheduling method provided by the present application;

[0082] Figure 4 A flow chart of another embodiment of the transshipment scheduling method provided by the present application;

[0083] Figure 5 A schematic diagram of the structure of the transfer scheduling device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0084] The following describes the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings. In the description of the embodiments of the present application, unless otherwise specified, " / " represents "or." For example, A / B can represent A or B. "And / or" in this document is merely a description of the association relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, or B exists alone.

[0085] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0086] Currently, road-rail transshipment is a widely used intermodal transport mode. It combines the advantages of road transport—flexibility, convenience, short response time, and ample capacity—with the advantages of the rail transport network, including its extensive network coverage, high stability, and high speed, achieving continuous, integrated transportation. Containerized freight transport, a mode of transport that combines cargo in containers, offers advantages such as reduced costs, improved efficiency, and smoother road-rail transshipment. Containerized road-rail transshipment organically integrates road and rail freight transport, reducing unnecessary resource waste, reducing empty vehicle mileage, optimizing operational processes, and leveraging resources to maximize the benefits of intermodal transport. Within the road transport process, transportation service procurement is a critical and important step. This process involves transport companies obtaining transportation services from intermodal transport operators based on their actual operational conditions and transportation needs. This process directly impacts the efficiency of road-rail transshipment and the profitability of all stakeholders.

[0087] However, in the existing technology, this complex method of procuring road-rail transshipment transportation services and coordinating truck transportation routes has the following shortcomings:

[0088] 1. Transport carriers of different sizes and natures have different bidding behaviors due to their different number of employees, service areas and operating conditions. Existing transport service procurement ignores the heterogeneous behaviors and bidding strategies among competitors.

[0089] 2. The existing research on the road-rail transshipment of containers does not take into account the interactive behavior of market participants, and cannot consider the synergy between different transport orders under different pricing strategies, resulting in waste of transport capacity and reduced transport efficiency.

[0090] 3. In the transport organization of road-rail transfer, bid generation and route decision issues are ignored, making it difficult to determine fleet management and the allocation and route decisions of trucks within the entire time range, resulting in a lack of effective allocation of transport capacity.

[0091] Therefore, how to provide an optimization method for truck allocation and route decision-making that can take into account the bidding behavior and bidding strategies of highway carriers and meet the time window requirements of each node is an urgent problem that technicians in this field need to solve.

[0092] Based on the above problems, an embodiment of the present application proposes a transfer scheduling method.

[0093] Now combined Figure 1-Figure 4 The above-mentioned transfer scheduling method is illustrated by way of example.

[0094] like Figure 1 The figure shows a flow chart of an embodiment of the transshipment scheduling method provided in the embodiment of the present application, which specifically includes the following steps:

[0095] Step 101 generates a bid transport order and discloses it to different types of carriers participating in the bidding. The bid transport order includes a road-rail transshipment transport order and / or a rail-road transshipment transport order. The bid transport order is generated based on the shipper's transport requirements, which include information such as the transport origin, destination, cargo volume, start time requirements, and destination time requirements. Different types of carriers include large and small transport companies.

[0096] Specifically, the multimodal transport operator can create a transport order to generate a transport order in the system, wherein the transport order can include a road-rail transshipment transport order and / or a rail-road transshipment transport order. It can be understood that after the transport order is generated in the system, the transport order can also be considered a bid transport order. Among them, the bid transport order can be generated based on the transport demand of the cargo owner (for example, the carrier of the cargo), and the transport demand can include multiple information such as the transport starting point, end point, freight volume, starting transport time requirement and delivery time requirement. Then, the multimodal transport operator can disclose the above-mentioned bid transport order to different types of carriers in accordance with relevant regulations and rules, so that the carriers can bid. Among them, the carriers can include two types, one is a large transport enterprise carrier, and the other is a small transport enterprise carrier.

[0097] Step 102: Based on the historical price pricing strategy and the combined price pricing strategy, a profit matrix of different types of carriers under the historical price pricing strategy and the combined price pricing strategy is constructed.

[0098] Specifically, after receiving the disclosed bid transport orders, large transport enterprise carriers and small transport enterprise carriers can bid for the disclosed bid transport orders. In a specific implementation, the bidding process of large transport enterprise carriers and small transport enterprise carriers can be modeled as an evolutionary game process. Large transport enterprise carriers and small transport enterprise carriers can adopt two strategies to construct profit matrices under different strategies. This allows large transport enterprise carriers and small transport enterprise carriers to obtain corresponding profit values when adopting different pricing strategies, thereby allowing large transport enterprise carriers and small transport enterprise carriers to bid based on the profit values. The above two pricing strategies can include a historical price pricing strategy and a combination price pricing strategy.

[0099] Next, specific methods of bidding based on a historical price pricing strategy and a combined price pricing strategy are exemplified.

[0100] Based on historical price pricing strategy: Since there are multiple transport routes from the starting point to the end point of the above-mentioned bid transport order, and the specific transport route cannot be determined at the time of bidding, the historical unit transport cost is considered to be the average of the historical unit transport costs of multiple transport routes, and the initial transport distance is the average of multiple transport routes. Taking the transport order as an example of a road-rail transshipment transport order, the revenue function can be represented by the following formula:

[0101]

[0102] in,

[0103]

[0104] Π is the profit function, is the unit bid price of carrier a's bid for road-rail transshipment transport order g, is the average unit cost of carrier a's bid for road-rail transshipment order g, ρ ag is the expected profit margin of carrier a's bid for road-rail transshipment order g, is the empty vehicle positioning cost of carrier a, is the probability that after the bidding road-rail transshipment transport order g arrives at the destination, its empty vehicle is repositioned and it wins another road-rail transshipment transport order, d vg is the average transportation distance of carrier a's bid for road-rail transshipment transport order g, N g is the number of containers bidding for the road-rail transshipment transport order g.

[0105] A pricing strategy based on a combined price: This strategy considers the synergy between existing transport orders and bid transport orders. In other words, once the existing transport order is completed, a truck is dispatched from the existing transport order to the bid transport order's starting point, using the shortest available empty truck positioning distance, to pick up the goods and complete the transport. This reduces empty truck positioning costs, and the price is determined based on the synergy value. For example, for a road-rail transshipment transport order, the synergy value can be calculated using the following formula:

[0106]

[0107] in, is the synergy value between carrier a’s existing road-rail transshipment transport order j and the bidding road-rail transshipment transport order g, is the unit bid price of the existing road-rail transshipment transport order j of carrier a, is the empty vehicle positioning distance from the end point of the existing road-rail transshipment transport order j to the starting point of the bidding road-rail transshipment transport order g for carrier a.

[0108] Since empty truck allocation must be considered in the combined pricing strategy, when the transportation tasks of existing road-rail transshipment transport orders are completed, the number of trucks allocated from the existing road-rail transshipment transport orders must be equal to the number of trucks (i.e., the number of containers) required for the bid road-rail transshipment transport orders. In this scenario, the revenue function can be expressed as follows:

[0109]

[0110] in,

[0111]

[0112]

[0113] It is 0 or 1. For example, when truck k with existing road-rail transshipment transport order j is deployed to serve the bidding road-rail transshipment transport order g, the value is 1; otherwise, it is 0. The unit bid price for all containers of the road-rail transshipment transport order g submitted by carrier a who adopts a combined price pricing.

[0114] Step 103 , by replicating the dynamic model, the profit matrix is solved to obtain the pricing strategy under the system stable state, and the target carrier is determined based on the bids of different types of carriers participating in the bidding corresponding to the pricing strategy under the system stable state.

[0115] Specifically, after constructing the profit matrix, the profit matrix can be solved by replicating the dynamic model. During the solution process, the asymptotic stability of the dynamic system is analyzed to obtain the pricing strategy under the stable state of the system. The target carrier with the best quotation can be selected to undertake the road transportation service of the container based on the quotations of large and small transport enterprise carriers participating in the bidding corresponding to the pricing strategy under the stable state of the system.

[0116] Step 104, based on the target carrier's pricing strategy quote under the system stable state, construct an objective function that minimizes the total cost and maximizes the benefit, consisting of the empty vehicle positioning cost, time value cost, transportation cost, storage cost, and penalty cost. Based on this objective function, generate a transshipment scheduling plan for the target carrier's pricing strategy under the system stable state for one or more bid transportation orders won by the target carrier.

[0117] Specifically, after the target carrier is determined, an objective function can be constructed based on the target carrier's pricing strategy quote under the system's stable state, with the goal of minimizing the total cost and maximizing benefits, consisting of empty vehicle positioning costs, time value costs, transportation costs, storage costs, and penalty costs. Then, based on this objective function, a transshipment scheduling plan based on the target carrier's pricing strategy under the system's stable state can be generated for one or more successful bid transportation orders from the target carrier. The objective function can be represented by the following formula:

[0118]

[0119] Among them, Z is the objective function, i is the winning road-rail transshipment transport order, and e is the winning rail-road transshipment transport order. It can be understood that the selection process of the target carrier corresponding to the bid rail-road transshipment transport order is the same as the selection process of the target carrier corresponding to the bid road-rail transshipment transport order. and is the unit bid price of carrier a’s winning road-rail transshipment transport order i or winning rail-road transshipment transport order e, d vi and d ve is the average transportation distance of carrier a’s winning road-rail transshipment transport order i or winning rail-road transshipment transport order e, N i or N e is the number of containers of the winning bid for road-rail transshipment transport order i or the winning bid for road-rail transshipment transport order e, and are the unit transportation costs of the carrier’s winning road-rail transshipment transport order i or winning rail-road transshipment transport order e when route r is selected, and The transportation distance when the truck serving the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e chooses route r, C0 is the carrier's empty truck positioning cost, d ji and d je D is the empty truck travel distance from the destination of truck k with existing road-rail transshipment transport order j to the starting point of the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e, kjir and D kjer is the storage cost of the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e, f kjir and f kjer is the penalty cost for winning the bid for road-rail transshipment transport order i or winning the bid for rail-road transshipment transport order e, t a is the unit time value cost, n i The upper limit of the time window for the truck that wins the bid for the road-rail transshipment transport order i to pick up the goods from the customer, is the time when truck k arrives at the destination of the existing road-rail transport order j, q e The upper limit of the time window for the truck that wins the bid for the railway-road transshipment transport order e to go to the railway station to pick up the goods. and It is 0 or 1. For example, when truck k with existing road-rail transshipment transport order j is deployed to serve the winning rail-road transshipment transport order i or the winning rail-road transshipment transport order e, and route r is selected to arrange container transportation, the value is 1; otherwise it is 0.

[0120] After the objective function is determined, the transshipment scheduling plan can be determined based on the scenarios of one or more winning transport orders.

[0121] Scenario 1: A winning transport order.

[0122] In scenario 1, if Figure 2 As shown, the determination of the above-mentioned transfer scheduling plan may specifically include the following steps:

[0123] Step 1040A, based on the time it takes for the truck to complete serving the existing road-rail transshipment transport order and the distance of the empty vehicle positioning, calculate the time it takes for each vehicle to complete the empty vehicle positioning for the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e. Specifically:

[0124]

[0125] Among them, t ji and t je are the empty vehicle positioning time of the existing road-rail transshipment transport order j corresponding to the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e, The end time of truck k completing the existing road-rail transshipment transport order j, and The time when truck k, which has an existing road-rail transshipment transport order j, serves the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e and selects route r to arrange container transportation, is when the truck arrives at the starting point of the corresponding transshipment transport order. and They are the latest times that the truck arrives at the starting point of the corresponding transshipment transport order.

[0126] Step 1040B, sort the vehicles according to the end time of their empty vehicle positioning. i The winning road-rail transshipment transport order i of containers, from the Nth i Start with a vehicle that can complete empty vehicle positioning, assuming it is the latest vehicle to arrive during the vehicle matching process. If the latest arriving vehicle is vehicle k, then N vehicles that arrived earlier must be selected. i - 1 vehicle for container transportation.

[0127] Specifically, the total number of trucks deployed from existing road-rail transshipment transport orders is equal to the number of containers in the transport order, for example,

[0128]

[0129]

[0130] All allocated trucks can only serve one winning road-rail transshipment transport order or one winning rail-road transshipment transport order and can only be used once. For example,

[0131]

[0132] Step 1040C, calculate the empty vehicle positioning cost and time value cost based on the given latest empty vehicle positioning time for each vehicle; when calling the transfer scheduling plan each time, directly sort according to the sum of the empty vehicle positioning cost and the time value cost.

[0133] Step 1040D: After selecting the vehicle that has completed the empty vehicle positioning the latest, the vehicle matching process is completed. In the vehicle matching process, vehicle selection is only related to the empty vehicle positioning cost and the time value cost, and has nothing to do with the subsequent path selection process. Therefore, the N vehicle with the smallest sum of the empty vehicle positioning cost and the time value cost is selected. i -1 vehicle.

[0134] Step 1040E: After vehicle matching is complete, route selection is performed. During the route selection process, the cost calculations are only related to the latest positioning time and the route selection, and are not related to the vehicle matching method. Therefore, given the latest empty vehicle positioning time, the path with the lowest total cost is selected through traversal.

[0135] Specifically, when the truck that wins the bid for road-rail transshipment transport order i arrives at the shipper later than the time window, the penalty cost is:

[0136]

[0137] Where f is the unit penalty cost.

[0138] When the truck that wins the bid for road-rail transshipment transport order i arrives at the railway station later than the time window, the storage cost incurred mainly comes from the waiting cost of waiting for the next train that meets the train capacity requirements before departure. The storage cost can be expressed as:

[0139]

[0140] Among them, D kjir The storage cost of the winning road-rail transshipment transport order i at the railway station, is the time window of the railway station corresponding to the winning road-rail transshipment transport order i, The time when truck k, which has a road-rail transshipment transport order j, wins the bid for road-rail transshipment transport order i and chooses route r to arrive at the railway station, t s is the free storage time at the railway station, s t is the unit storage cost at the railway yard.

[0141] The weight of the container cannot exceed the capacity of the available train cars. If the container exceeds the train capacity, it must wait for the next train that can meet the train capacity requirements before it can depart. The resulting storage cost is expressed as:

[0142]

[0143] Among them, q i is the weight of the container that won the bid for road-rail transshipment transport order i, Q oi is the weight of other cargoes that the winning road-rail transshipment order i arrives at the railway station, Qi The train capacity of the railway station to which the winning bidder for the road-rail transshipment transport order i arrives.

[0144] When the truck of the winning railway-highway transshipment transport order e arrives at the railway station later than the time window, the storage cost incurred is expressed as:

[0145]

[0146] When the truck that wins the bid for the railway-highway transshipment transport order e arrives at the shipper later than the time window, the penalty cost is expressed as:

[0147]

[0148] in, The time when truck k, which has an existing road-rail transshipment transport order j, wins the bid for the road-rail transshipment transport order e and chooses route r to arrive at the cargo owner, b e The upper limit of the delivery time window for the customer corresponding to the winning rail-road transfer transport order e.

[0149] Since most companies have a planned inventory consumption cycle, receiving goods too early or too late will increase storage costs. Therefore, receiving goods can be based on the customer's time satisfaction, where the customer's time satisfaction can be expressed as:

[0150]

[0151]

[0152] in, is customer satisfaction, h is the constraint value of customer satisfaction, The period of inventory consumption for the enterprise that won the bid for the railway-highway transshipment transport order e. During this period, the enterprise only retains the inventory required to maintain normal operations. As the inventory is consumed, the unit inventory cost generated after the goods are put into storage decreases, and time satisfaction increases accordingly. The best delivery time, time satisfaction is 100%, The safety stock consumption period of the enterprise, when the receipt time is later than Safety stock will begin to be consumed when the product is delivered. At this time, customers will be more sensitive to inventory consumption and their satisfaction will drop significantly.

[0153] After completing the vehicle matching and routing process in step 1040F, the vehicle matching and routing method for the given minimum positioning time and time window requirements for each node are obtained. The corresponding transportation cost, penalty cost, and storage cost are also calculated. The vehicle matching and routing method that minimizes the total cost is the optimal vehicle scheduling method and routing for the transport order.

[0154] Scenario 2: Multiple winning bids for road-rail transshipment transport orders or multiple winning bids for rail-road transshipment transport orders.

[0155] If there are multiple winning road-rail transshipment transport orders or multiple winning rail-road transshipment transport orders, the vehicle allocation methods for each winning road-rail transshipment transport order or multiple winning rail-road transshipment transport orders must be coordinated to achieve the optimal solution. Considering that the vehicle scheduling method within each winning road-rail transshipment transport order or winning rail-road transshipment transport order does not affect the scheduling cost of other winning road-rail transshipment transport orders or winning rail-road transshipment transport orders, dynamic programming is used to achieve this.

[0156] In the case of scenario 2, if Figure 3 As shown, the determination of the above-mentioned transfer scheduling plan may further include the following steps:

[0157] Step 1040G, dividing the states. Considering that the vehicle allocation method between different winning road-rail transshipment transport orders or winning rail-road transshipment transport orders will not affect the allocation costs of other winning road-rail transshipment transport orders or winning rail-road transshipment transport orders, the solution of the multiple winning road-rail transshipment transport orders or multiple winning rail-road transshipment transport orders is divided into several stages according to the sequential characteristics of the multiple winning road-rail transshipment transport orders or multiple winning rail-road transshipment transport orders.

[0158] Step 1040H, determine the state and state variables. For all the given winning road-rail transshipment transport orders i and winning rail-road transshipment transport orders e, let’s assume that the solver has N i , N e elements, and use N to place the transport orders in the given order i +N e The bits represent the current solution status, where if the mth bit is 1, it means that the vehicle scheduling for the mth order has been solved, otherwise it is 0. Each state record corresponds to the vehicle scheduling method of the optimal solution.

[0159] Step 1040I determines the decision and state transition. States with a Hamming distance of 1 are adjacent states. That is, the previous state can be changed to the next state by applying the same transport order vehicle scheduling algorithm to a specific transport order. For example, state 010100 can be changed to state 011100 by applying the same transport order vehicle scheduling optimization algorithm to transport order 3. The optimal solution for each state can be obtained by applying the same transport order vehicle scheduling optimization algorithm to its adjacent states. For example, the optimal solution for state 1100 can be obtained by applying the same transport order optimization algorithm to states 1000 and 0100, respectively. The solution with the minimum cost is the optimal solution for state 1100.

[0160] Step 1040J: Through dynamic programming, the optimal solution corresponding to the target state (all 1s) is the optimization algorithm result. At this time, the algorithm goal is to transfer from the initial state (all 0s) to the target state (all 1s) with the minimum cost.

[0161] In the first-stage model of this embodiment, basic information about the shipper's transportation needs and transport orders is first obtained. The multimodal transport operator, in accordance with relevant regulations and rules, discloses the tendered items and their detailed information to each road carrier. Each road carrier bids in an open or sealed format, competing fairly using two bidding strategies. The road carrier's bidding process is modeled as an evolutionary game. By solving a replicated dynamic model and analyzing the asymptotic stability of the dynamic system, an evolutionary stability strategy is derived for the system's stable state. Based on the bids received from different carriers under this evolutionary stability strategy, the carrier with the best bid is selected to undertake the road transport task. In the second-stage model, by rationally arranging vehicle allocation and optimizing routes for container transportation, a road-rail transfer vehicle allocation and collaborative route optimization model is constructed with the goal of minimizing empty vehicle positioning costs, time value costs, transportation costs, storage costs, and penalty costs, and maximizing benefits, with the time windows of each node as constraints, to determine the transfer scheduling plan; thereby, the empty vehicle positioning costs and fleet management can be minimized, and the time window constraints of the road-rail transfer process can be considered as a whole, reducing transportation costs while improving overall transportation efficiency, making the mutual benefit of carriers and multimodal transport operators a reality, and maximizing the interests of both parties.

[0162] like Figure 4 The figure shows a flow chart of another embodiment of the road-rail transport scheduling method provided in the embodiment of the present application. Figure 4 In the embodiment shown, step 103 may specifically include the following steps:

[0163] Step 1031, determining the probability of large-scale transport enterprise carriers and small-scale transport enterprise carriers selecting different pricing strategies, and determining the average expected revenue values of large-scale transport enterprise carriers and small-scale transport enterprise carriers based on the probabilities of selecting different pricing strategies.

[0164] Specifically, suppose that the probability of a small transport enterprise carrier selecting a historical price pricing strategy in a game is x, and the probability of selecting a combination price pricing strategy is 1-x; suppose that the probability of a large transport enterprise carrier selecting a historical price pricing strategy in a game is y, and the probability of selecting a combination price pricing strategy is 1-y.

[0165] The average expected revenue of large and small transport carriers can be calculated using the following formula:

[0166]

[0167] Among them, U SP is the average expected profit value of small transport carriers, U LP is the average expected profit value of large transport carriers, U SP1 is the expected profit value of a small transport carrier when it adopts the historical price pricing strategy, U SP2 is the expected profit value of small transport carriers when adopting a combined price pricing strategy, U LP1 is the expected profit value of a large transport enterprise carrier when adopting the historical price pricing strategy, U LP2 The expected profit value when a large transport enterprise carrier adopts a combined price pricing strategy. It is understandable that the above expected profit value can be obtained by calculating the profit function in the above embodiment.

[0168] Step 1032: By solving the replicated dynamic model, the asymptotic stability of the dynamic system is analyzed to obtain the stable state of each participant in the game. The replicated dynamic model is determined by the average expected revenue of large-scale transport enterprise carriers and small-scale transport enterprise carriers.

[0169] Specifically, in a pre-set replication dynamic model of n groups, assuming that each participant chooses strategy m to play the game, the proportion of participants who choose strategy V in the group changes over time in a dynamic system of continuous game, learning, and imitation. The rate of change is determined by the number of participants in the group and the difference between their own interests in the group and the average interests of the group. The pre-set replication dynamic model can be represented by the following equation:

[0170]

[0171] By solving the replication dynamic model and analyzing the asymptotic stability of the dynamic system, we can obtain the stable state of each participant in the game. From the theory of dynamic stability, we know that the system equilibrium point of the group evolution game between two types of transport carriers (for example, small transport carriers and large transport carriers) must satisfy: F (x) =0, F (y) =0, that is, the equilibrium point of the game system is obtained.

[0172] The specific process of the aforementioned system asymptotic stability analysis can be as follows: for the dynamic system being processed, the system's asymptotic stability point refers to the point where the strategy combination corresponding to the equilibrium point is stable. When repeated games are played, the system will eventually converge to this equilibrium point, forming this strategy combination. This equilibrium point is considered an asymptotically stable point. The Jacobian matrix can be used to determine the stability of the system.

[0173] According to the principles of evolutionary game theory, the local stability of an equilibrium point can be expressed by the determinant det(J) and trace tr(J) of the corresponding Jacobian matrix J. If and only if det(J) > 0 and tr(J) < 0, the equilibrium point is stable, and the replicating dynamic system tends to a stable state.

[0174] According to the replicated dynamic equation, the Jacobian matrix J can be obtained as:

[0175]

[0176] Step 1033, determine the optimal pricing strategy for large transport enterprise carriers and small transport enterprise carriers in a stable state, and select the carrier with the lowest quotation as the target carrier by comparing the quotations of large transport enterprise carriers and small transport enterprise carriers under the optimal pricing strategy.

[0177] Specifically, by calculating the determinant det(J) and trace tr(J) of the equilibrium Jacobian matrix J, we analyze the impact of various revenue values on system stability under different pricing strategies and use these revenue values to determine the stability of the equilibrium. If the equilibrium is stable, the evolutionary game between the various parties reaches a stable strategy combination at that point, forming an evolutionary stable state. By analyzing the location of the stable equilibrium, we determine the optimal bidding strategies for large and small carriers. By comparing the bids of large and small carriers under the optimal bidding strategies, we select the carrier with the lowest bid to transport the order container.

[0178] In this embodiment, the profit matrix is solved by replicating the dynamic equation and the stability of the system is analyzed to obtain the evolutionary stable strategies corresponding to the two types of carriers under the stable state of the system. The carrier with the best quotation is selected based on the quotation results of the two types of carriers, thereby more accurately selecting the optimal carrier.

[0179] Figure 5 This is a structural diagram of an embodiment of the transfer scheduling device of this application, as shown in FIG. Figure 5 As shown, the above-mentioned transshipment scheduling device 50 may include: an order generating module 51, a constructing module 52, a determining module 53 and a solution generating module 54; wherein,

[0180] The order generation module 51 is configured to generate a bid transport order and disclose the bid transport order to different types of carriers participating in the bidding. The bid transport order includes a road-rail transshipment transport order and / or a rail-road transshipment transport order. The bid transport order is generated based on the cargo owner's transport demand, which includes multiple information including the transport starting point, end point, cargo volume, start transport time requirement, and destination delivery time requirement. The different types of carriers include large transport enterprise carriers and small transport enterprise carriers.

[0181] A construction module 52 is configured to construct, based on the historical price pricing strategy and the combined price pricing strategy, a profit matrix of the different types of carriers participating in the bidding under the historical price pricing strategy and the combined price pricing strategy;

[0182] a determination module 53 for solving the revenue matrix by replicating the dynamic model to obtain a pricing strategy under a system stable state, and determining a target carrier based on the bids of different types of carriers participating in the bidding corresponding to the pricing strategy under the system stable state;

[0183] The solution generation module 54 is used to construct an objective function with the objectives of minimizing the total cost consisting of empty vehicle positioning cost, time value cost, transportation cost, warehousing cost and penalty cost and maximizing benefits based on the quotation of the pricing strategy of the target carrier in the stable state of the system, and generate a transshipment scheduling solution of the pricing strategy of the target carrier in the stable state of the system based on the objective function for one or more bid transportation orders won by the target carrier.

[0184] Through the description of the above embodiments, those skilled in the art will clearly understand that for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0185] The functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0186] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as flash memory, mobile hard disk, read-only memory, random access memory, magnetic disk or optical disk.

[0187] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application shall be covered by the scope of protection of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection of the claims.

Claims

1. A transshipment scheduling method, characterized in that: The method comprises: Generating a bid transport order and disclosing the bid transport order to different types of carriers participating in the bidding; wherein the transport order includes a road-rail transshipment transport order and / or a rail-road transshipment transport order, and the bid transport order is generated based on the cargo owner's transport demand, which includes multiple information including the transport starting point, end point, cargo volume, start transport time requirement, and destination delivery time requirement; the different types of carriers include large transport enterprise carriers and small transport enterprise carriers; Based on the historical price pricing strategy and the combined price pricing strategy, constructing a profit matrix for the different types of carriers participating in the bidding under the historical price pricing strategy and the combined price pricing strategy; Solving the profit matrix by replicating the dynamic model to obtain a pricing strategy under a system stable state, and determining a target carrier based on the bids of different types of carriers participating in the bidding corresponding to the pricing strategy under the system stable state; Based on the target carrier's pricing strategy quote under the system's stable state, construct an objective function with the goal of minimizing the total cost consisting of empty vehicle positioning cost, time value cost, transportation cost, storage cost, and penalty cost, and maximizing benefits; and based on the objective function, generate a transshipment scheduling plan for the target carrier's pricing strategy under the system's stable state for one or more successful bid transportation orders of the target carrier; The historical price pricing strategy includes the profit function: in, The Π is the profit function, the is the unit bid price of carrier a's bid for road-rail transshipment transport order g, is the average unit cost of carrier a's bid for road-rail transshipment order g, ρ ag is the expected profit margin of carrier a's bid for road-rail transshipment order g, is the empty vehicle positioning cost of carrier a, is the probability that after the bidding road-rail transshipment transport order g arrives at the destination, its empty vehicle is repositioned and it wins another road-rail transshipment transport order, d vg is the average transportation distance of carrier a's bid for road-rail transshipment transport order g, N g The number of containers bidding for road-rail transshipment transport order g; The combined price pricing strategy includes the profit function: Among them, the The unit bid price for all containers of the road-rail transshipment transport order g submitted by carrier a using a combined price; described is the synergy value between carrier a’s existing road-rail transshipment transport order j and the bidding road-rail transshipment transport order g, is 0 or 1, is the unit bid price of the existing road-rail transshipment transport order j of carrier a, is the empty vehicle positioning distance from the end point of the existing road-rail transshipment transport order j to the starting point of the bidding road-rail transshipment transport order g of carrier a; Solving the revenue matrix by replicating the dynamic model to obtain a pricing strategy under a system stable state, and determining a target carrier based on bids of different types of carriers participating in the bidding corresponding to the pricing strategy under the system stable state includes: Determine the probability that the large-scale transport enterprise carrier and the small-scale transport enterprise carrier select different pricing strategies, and determine the average expected revenue value of the large-scale transport enterprise carrier and the small-scale transport enterprise carrier based on the probability of selecting different pricing strategies; wherein the average expected revenue value is calculated by the following formula: U SP is the average expected profit value of the small transport enterprise carrier, U LP is the average expected profit value of the large transport enterprise carrier, U SP1 is the expected profit value of the small transport enterprise carrier when adopting the historical price pricing strategy, U SP2 is the expected profit value of the small transport enterprise carrier when adopting the combined price pricing strategy, U LP1 is the expected profit value of the large transport enterprise carrier when adopting the historical price pricing strategy, U LP2 The expected profit value of the large-scale transport enterprise carrier when adopting the combined price pricing strategy; By solving the replication dynamic model, the asymptotic stability of the dynamic system is analyzed, and the stable state of each participant in the game is obtained; wherein the replication dynamic model is determined by the average expected revenue value of the large transportation enterprise carrier and the small transportation enterprise carrier; the replication dynamic model is represented by the following equation: Determining the optimal pricing strategy for the large transport enterprise carrier and the small transport enterprise carrier in a steady state, and selecting the carrier with the lowest bid as the target carrier by comparing the bids of the large transport enterprise carrier and the small transport enterprise carrier under the optimal pricing strategy; The objective function is: Wherein, Z is the objective function, i is the winning bid for the road-rail transshipment transport order, e is the winning bid for the road-rail transshipment transport order, and is the unit bid price of carrier a’s winning road-rail transshipment transport order i or winning rail-road transshipment transport order e, d vi and d ve is the average transportation distance of carrier a’s winning road-rail transshipment transport order i or winning rail-road transshipment transport order e, N i or N e is the number of containers of the winning bid for road-rail transshipment transport order i or the winning bid for road-rail transshipment transport order e, and are the unit transportation costs of the carrier’s winning road-rail transshipment transport order i or winning rail-road transshipment transport order e when route r is selected, and The transportation distance when the truck serving the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e chooses route r, C0 is the carrier's empty truck positioning cost, d ji and d je D is the empty truck travel distance from the destination of truck k with existing road-rail transshipment transport order j to the starting point of the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e, kjir and D kjer is the storage cost of the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e, f kjir and f kjer is the penalty cost for winning the bid for road-rail transshipment transport order i or winning the bid for rail-road transshipment transport order e, t a is the unit time value cost, n i The upper limit of the time window for the truck that wins the bid for the road-rail transshipment transport order i to pick up the goods from the customer, The time q when truck k arrives at the destination of the existing road-rail transport order j e The upper limit of the time window for the truck that wins the bid for the railway-road transshipment transport order e to go to the railway station to pick up the goods. and is 0 or 1; The generating of a transshipment scheduling scheme for the target carrier's pricing strategy in the system stable state based on the objective function for one or more successful bid transportation orders of the target carrier comprises: If the target carrier wins a bid for a road-rail transshipment transport order or a bid for a rail-road transshipment transport order, the time when each vehicle's empty vehicle positioning ends is calculated based on the time it takes for the truck to complete serving the existing road-rail transshipment transport order and the distance of the empty vehicle positioning; Sort the vehicles according to the end time of empty vehicle positioning. i The winning road-rail transshipment transport order i of containers, from the Nth i Starting from a vehicle that can complete empty vehicle positioning, it is assumed that it is the latest vehicle to arrive during the vehicle matching process. If the latest arriving vehicle is vehicle k, then N vehicles that arrive earlier must be selected. i - 1 vehicle for container transportation; Based on the latest empty vehicle positioning time of each vehicle, the empty vehicle positioning cost and time value cost are calculated; each time the transfer scheduling plan is called, the empty vehicle positioning cost and time value cost are directly sorted; After selecting the vehicle that completes the empty vehicle positioning the latest, the vehicle matching process is completed; in the vehicle matching process, the N vehicles with the smallest sum of the empty vehicle positioning cost and the time value cost are selected. i - 1 vehicle; After completing vehicle matching, route selection is performed. During the route selection process, given the latest empty vehicle positioning time, the route with the minimum total cost is traversed and selected. After completing the vehicle matching and route selection process, the vehicle matching and route selection methods under the given latest positioning time and the time window requirements of each node are obtained. At the same time, the corresponding transportation cost, penalty cost and warehousing cost can be calculated. The vehicle matching and route selection method corresponding to the minimum total cost is determined as the optimal vehicle scheduling method and route selection for the winning road-rail transshipment transport order; The generating of a transshipment scheduling scheme for the target carrier's pricing strategy in the system stable state based on the objective function for one or more successful bid transportation orders of the target carrier comprises: If the target carrier wins the bid for multiple road-rail transshipment transport orders or multiple rail-road transshipment transport orders, dividing the solution of the multiple winning road-rail transshipment transport orders or the multiple rail-road transshipment transport orders into several stages according to the sequence characteristics of the multiple winning road-rail transshipment transport orders or the multiple rail-road transshipment transport orders; For all the given winning road-rail transshipment transport orders i and winning rail-road transshipment transport orders e, let the solvers have N i , N e elements, and use N to sort the transport orders in the given order. i +N e bits represent the current solution state, where each state record corresponds to the vehicle dispatching method of the optimal solution; The optimal solution for each state can be obtained by calling the transfer scheduling scheme of its adjacent states; among them, the states with a Hamming distance of 1 are adjacent states; Through dynamic programming, the optimal solution corresponding to the target state is determined as the optimization algorithm result, where the algorithm goal is to transfer from the initial state to the target state with the minimum cost.

2. The method according to claim 1, characterized in that The time when the empty vehicle positioning of each vehicle ends is calculated by the following formula: Among them, t ji and t je are the empty vehicle positioning time of the existing road-rail transshipment transport order j corresponding to the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e, The end time of truck k completing the existing road-rail transshipment transport order j, and The time when truck k, which has an existing road-rail transshipment transport order j, serves the winning road-rail transshipment transport order i or the winning rail-road transshipment transport order e and selects route r to arrange container transportation, is when the truck arrives at the starting point of the corresponding transshipment transport order. and They are the latest times that the truck arrives at the starting point of the corresponding transshipment transport order.

3. The method according to claim 1, characterized in that The number of vehicles deployed to serve the winning road-rail transshipment transport order i and the winning rail-road transshipment transport order e is determined by the following formula: Among them, the total number of trucks allocated from the existing road-rail transshipment transport orders is equal to the number of containers in the transport order. All allocated trucks can only serve one winning road-rail transshipment transport order or one winning rail-road transshipment transport order, and can only be used once.

4. The method according to claim 2, characterized in that In the path selection process, under the premise of a given latest empty vehicle positioning time, the path with the minimum total cost of traversal path selection includes: When the truck that wins the bid for road-rail transshipment transport order i arrives at the shipper later than the time window, the penalty cost is: When the truck that wins the bid for road-rail transshipment transport order i arrives at the railway station later than the time window, the storage cost incurred is: The weight of the container cannot exceed the capacity of the available train cars. If the container exceeds the train capacity, it must wait for the next train that can meet the train capacity requirements before it can depart. The resulting storage cost is expressed as: When the truck of the winning railway-road transshipment transport order e arrives at the railway station later than the time window, the storage cost incurred is expressed as: When the truck that wins the bid for the railway-highway transshipment transport order e arrives at the shipper later than the time window, the penalty cost is expressed as: The goods are received based on the customer's time satisfaction, where the customer's time satisfaction is expressed as: Among them, f is the unit penalty cost, D kjir The storage cost of the winning road-rail transshipment transport order i at the railway station, is the time window of the railway station corresponding to the winning road-rail transshipment transport order i, The time when truck k, which has a road-rail transshipment transport order j, wins the bid for road-rail transshipment transport order i and chooses route r to arrive at the railway station, t s is the free storage time at the railway station, s t is the unit storage cost of the railway station, q i is the weight of the container that won the bid for road-rail transshipment transport order i, Q oi Q is the weight of other cargoes that the winning road-rail transshipment transport order i arrives at the railway station, i The train capacity of the railway station to which the winning road-rail transshipment transport order i is delivered, The time when truck k, which has an existing road-rail transshipment transport order j, wins the bid for the road-rail transshipment transport order e and chooses route r to reach the cargo owner, b e The upper limit of the delivery time window for the customer corresponding to the winning railway-highway transport order e, is customer satisfaction, h is the constraint value of customer satisfaction, The enterprise turnover inventory consumption period corresponding to the winning railway-highway transshipment transport order e; The best delivery time, It is the enterprise's safety stock consumption period.

5. A transport scheduling device, characterized in that: include: One or more functional modules, wherein the one or more functional modules are used to execute the transshipment scheduling method according to any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is run on a computer, the transshipment scheduling method according to any one of claims 1 to 4 is executed.

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