Transport route planning method and device

Abstract

The present application provides a method and apparatus for transport route planning, including: receiving multiple order information, wherein the order information includes transport start and end stations and transport requirements; determining an initial path including the main warehouse and forward warehouses in the multiple order information; using a destruction operator to delete a set number of forward warehouses from the initial path to obtain a destroyed path; using a repair operator to determine the importance of the deleted forward warehouses, using the importance as the selection probability, and sequentially inserting the deleted forward warehouses into the optimal position of the destroyed path to obtain an updated path; if the target value is not greater than the target value of the initial path, using the updated path as the initial path, returning to the step of deleting the set number of forward warehouses from the initial path through the destruction operator, and looping until the final path is obtained; the importance is determined by the transport requirements in the order information corresponding to the forward warehouses; and the target value is determined based on the transport cost of the path. The method is used to achieve fully automated transport route planning and improve the intensity and efficiency of transport route optimization.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a transportation route planning method and device. Background Art

[0002] With the continuous development of computer technology, e-commerce has also been gradually expanding. In e-commerce, people place orders online or offline, and transport personnel pick up goods from warehouses and transport them to their destinations. During this process, replenishing warehouse inventory is extremely important.

[0003] In existing technology, warehouses are generally divided into large warehouses and forward warehouses, with large warehouses replenishing and storing goods in each forward warehouse. A transportation management system (TMS) can provide an operation interface, allowing staff to select transportation tools, large warehouses, and forward warehouses on the operation interface. The transportation management system then determines the optimal transportation route based on the selected transportation tools, large warehouses, and forward warehouses. However, this method is extremely time-consuming and labor-intensive to manually operate in scenarios with large orders, and the resulting transportation route optimization is insufficient, resulting in a certain waste of transportation costs.

[0004] There is an urgent need for a transport path planning method and device to achieve fully automated transport path planning, improve the transport path optimization intensity, and improve the transport path optimization efficiency. Summary of the Invention

[0005] The embodiments of the present application provide a transport path planning method and device for realizing fully automated transport path planning, improving the transport path optimization intensity, and improving the transport path optimization efficiency.

[0006] In a first aspect, an embodiment of the present application provides a transportation route planning method, the method comprising:

[0007] Receive multiple order information, each of which includes transportation starting and ending stations and transportation requirements; the transportation starting and ending stations include a large warehouse as the starting point and a forward warehouse as the end point;

[0008] Determine an initial path based on the multiple order information, where the initial path includes the major warehouses and forward warehouses in the multiple order information;

[0009] A set number of forward warehouses are deleted from the initial path by a destruction operator to obtain a destroyed path; the importance of the deleted forward warehouses is determined by a repair operator, and the importance is used as the selection probability to insert the deleted forward warehouses into the optimal position of the destroyed path in sequence to obtain an updated path; if the target value of the updated path is not greater than the target value of the initial path, the updated path is used as the initial path, and the step of deleting the set number of forward warehouses from the initial path by the destruction operator is returned to, and the cycle is repeated until the final path is obtained; wherein the importance is determined by the transportation requirements in the order information corresponding to the forward warehouse; and the target value is determined according to the transportation cost of the path.

[0010] In the above method, multiple order information can be received, and the final path can be determined based on the transportation starting and ending stations and transportation requirements in the multiple order information. In this process, the importance of the forward warehouse is used as a reference factor for initial path optimization. The higher the importance of the forward warehouse, the greater the transportation requirements such as vehicle volume and vehicle cost of the initial path - the greater the transportation cost. Under certain vehicle volume and vehicle cost in the initial path, the forward warehouse with high importance is taken as a relatively priority optimization object, which effectively improves the optimization degree and efficiency. In the application, it can speed up the speed of obtaining the final path and improve the optimization of obtaining the final path.

[0011] Optionally, determining an initial path according to the plurality of order information includes:

[0012] Determining at least one temporary route based on the plurality of order information based on a mileage saving method;

[0013] Determining the transportation cost and path accessibility of each temporary path based on the transportation requirements in the plurality of order information, wherein the path accessibility is determined based on the distance between each forward warehouse in the path, and the closer the distance between each forward warehouse in the path, the higher the path accessibility;

[0014] For each temporary path, the transportation cost and path accessibility of the temporary path are substituted into the objective function to obtain the target value of the temporary path;

[0015] A temporary path with the lowest target value is determined from the at least one temporary path as the initial path.

[0016] In the above method, before optimizing the initial path using the destruction and repair operators, the distance relationship between each forward warehouse and the main warehouse in multiple order information is calculated based on a mileage-saving algorithm to determine multiple temporary paths with shorter routes. The transportation cost and path accessibility of each of these temporary paths are then calculated and substituted into the objective function to obtain the target value for each temporary path. The temporary path with the lowest target value is then used as the initial path. This simple optimization makes the initial path the result of a simple optimization. This simple optimization can accelerate the efficiency of subsequent optimization using the repair and destruction operators and improve the final optimization effect. Specifically, the final path has a low transportation cost and a high path accessibility between the main warehouse and the forward warehouse, facilitating cargo transportation.

[0017] Optionally, determining the transportation cost of each temporary path according to the transportation requirements in the plurality of order information includes:

[0018] For any temporary path, determine the distance between each node in the temporary path according to the road network data; each node includes a large warehouse and a forward warehouse;

[0019] Allocate a vehicle according to the transportation requirements in each order information;

[0020] The transportation cost of the temporary path is determined based on the unloading time of each forward warehouse in the order information, the mileage price of the vehicle type of the assigned vehicle, the city mileage price of the city involved, and the distance between the nodes.

[0021] In this method, the distance between each node in the temporary route can be accurately calculated based on road network data. Vehicles are then assigned based on the transportation requirements of each order. For example, vehicles can be assigned to orders based on information such as cargo type and quantity to ensure that the transportation requirements of each order are met. The transportation cost of the temporary route is then determined based on the mileage rate for the vehicle type, the city mileage rate for the city involved, the unloading time, and the distance between each node. This approach, by integrating multiple factors, yields a highly accurate transportation cost for the temporary route.

[0022] Optionally, the destruction operator includes multiple types; before deleting a set number of forward warehouses from the initial path through the destruction operator, the method further includes:

[0023] In each round of path optimization, the destruction operator used for path optimization is selected using the roulette wheel method;

[0024] After taking the updated path as the initial path, the method further includes:

[0025] After the current round of path optimization is completed, the score of the destruction operator is updated according to the updated path, and the score is used for the subsequent roulette wheel method to select the probability parameter of the destruction operator.

[0026] In the above method, during the initial path optimization process, multiple destructive operators are used for path optimization. These destructive operators can be selected for path optimization using a roulette wheel method. After path optimization is complete, the optimization effect of the destructive operator is determined based on the final path obtained from the initial path optimization. A score is then calculated for the destructive operator, and this score serves as a probability parameter for subsequent roulette wheel selection of the destructive operator. In this way, destructive operators with good path optimization effects receive high scores, corresponding to a high probability of being selected by the roulette wheel method. Destructive operators with poor path optimization effects receive low scores, corresponding to a low probability of being selected by the roulette wheel method. This process not only optimizes the initial path, but also the optimization algorithm for the initial path, improving optimization efficiency.

[0027] Optionally, the destruction operator includes at least one of a first random removal operator, a second random removal operator, a cost removal operator, a path removal operator and a time removal operator; wherein, the first random removal operator is used to randomly remove the forward warehouse in the initial path, the second random removal operator is used to randomly remove the sub-path in the initial path, the cost removal operator is used to remove the forward warehouse with high transportation service demand in the initial path, the path removal operator is used to randomly remove part of the path in the sub-path in the initial path, and the time removal operator is used to remove the forward warehouse with short transportation time requirement in the initial path.

[0028] In the above method, the first random removal operator is used to randomly remove a forward warehouse from the initial path. The repair operator is then used to insert the randomly removed forward warehouse into the optimal position of the damaged initial path (e.g., the transport cost and path accessibility of the updated path obtained by inserting the randomly removed forward warehouse into the optimal position of the damaged initial path can be substituted into the objective function to obtain the lowest target value). This results in an updated path. In other words, the advantage of the first random removal operator is that each forward warehouse in the initial path has an equal probability of being removed, and each forward warehouse in the initial path has a chance of being optimized. The second random removal operator is used to remove a subpath from the initial path. The repair operator is then used to insert the randomly removed subpath into the optimal position of the damaged initial path (e.g., the transport cost and path accessibility of the updated path obtained by inserting the randomly removed subpath into the optimal position of the damaged initial path can be substituted into the objective function to obtain the lowest target value). This results in an updated path. In other words, the advantage of the second random removal operator is that each subpath in the initial path has an equal probability of being removed. During the path optimization process, complete subpaths are removed as units, and each subpath in the initial path has a chance of being optimized. The cost removal operator removes forward warehouses with high transport service demand from the initial path. The repair operator then inserts these removed forward warehouses into the optimal position of the damaged initial path. This optimizes these forward warehouses for the fastest possible transport service demand, maximizing the optimization of the target values ​​of the initial path's transport cost and path accessibility within the objective function, thereby improving path optimization efficiency. The path removal operator randomly removes portions of a subpath from the initial path. The repair operator then inserts these randomly removed subpaths into the optimal position of the damaged initial path to obtain an updated path. The advantage of the random path removal operator is that it selects complete subpaths for removal and then optimizes the selected subpaths, thereby significantly improving optimization efficiency. The time removal operator removes forward warehouses with close transport time requirements from the initial path. The repair operator then inserts these forward warehouses into the optimal position of the damaged initial path to obtain an updated path. This ensures that transport time requirements between adjacent forward warehouses in the updated path are not too closely spaced, effectively preventing problems such as untimely unloading and delivery.

[0029] Optionally, the repair operator includes multiple types. Before determining the importance of the deleted forward warehouse through the repair operator, it also includes:

[0030] In each round of path optimization, the repair operator used for path optimization is selected using the roulette wheel method;

[0031] After taking the updated path as the initial path, the method further includes:

[0032] After the current round of path optimization is completed, the score of the repair operator is updated according to the updated path, and the score is used for the subsequent roulette wheel method to select the probability parameter of the repair operator.

[0033] In the above method, during the initial path optimization process, multiple repair operators are available for path optimization. These operators can be selected for path optimization using a roulette wheel method. After path optimization is complete, the optimization effect of the repair operator is determined based on the final path obtained from the initial path optimization. A score is then calculated for the repair operator, and this score serves as a probability parameter for subsequent roulette wheel selection. In this way, repair operators with good path optimization effects receive high scores, corresponding to a high probability of being selected by the roulette wheel method. Repair operators with poor path optimization effects receive low scores, corresponding to a low probability of being selected by the roulette wheel method. This process not only optimizes the initial path, but also the optimization algorithm for the initial path, improving optimization efficiency.

[0034] Optionally, before determining the initial path according to the plurality of order information, the method further includes:

[0035] Determining that there is order information among the multiple order information whose transportation service demand exceeds a first preset threshold, splitting the order information exceeding the first preset threshold into at least two order information, where the transportation service demand of each of the split order information is lower than the first preset threshold; or

[0036] Determine that there is order information among the multiple order information whose transportation service demand is lower than a second preset threshold, and combine the order information below the second preset threshold with one or more other order information into one order information, and the transportation service demand of the combined order information is lower than the first preset threshold.

[0037] In the above method, if the transportation service demand in the order information exceeds a first preset threshold, the transportation service capacity of the current individual order cannot effectively support the order information. The order information needs to be split into at least two order information so that each resulting order information meets the provided transportation service capacity. For example, transportation service demand can include relevant information such as transportation manpower and vehicle transportation requirements. If the transportation manpower, vehicle capacity, and other requirements in the transportation service demand of a single order information exceed the upper limit of the transportation service demand assigned to each order information - the first preset threshold, this may lead to problems with the scheduling of transportation vehicles and transportation manpower. The order splitting solution can effectively prevent this from occurring. Correspondingly, if there are order information with transportation service demand below a second preset threshold among multiple order information, transportation resources may be wasted. For example, if the transportation service demand in the order information is below the second preset threshold, the transportation service capacity (transportation manpower, vehicle capacity) allocated for each order information will be idle, wasting transportation resources. Combining the order information below the second preset threshold into a single order information can effectively prevent this waste of transportation resources.

[0038] In a second aspect, an embodiment of the present application provides a transport path planning device, the device comprising:

[0039] A transceiver module is used to receive multiple order information, each of which includes a transportation start and end station and transportation requirements; the transportation start and end stations include a large warehouse as a starting point and a forward warehouse as a destination;

[0040] A processing module, configured to determine an initial path according to the plurality of order information, wherein the initial path includes all major warehouses and all forward warehouses in the plurality of order information;

[0041] The processing module is also used to delete a set number of forward warehouses from the initial path through a destruction operator to obtain a destroyed path; determine the importance of the deleted forward warehouses through a repair operator, and use the importance as the selection probability to insert the deleted forward warehouses into the optimal position of the destroyed path in sequence to obtain an updated path; if the target value of the updated path is not greater than the target value of the initial path, then use the updated path as the initial path, return to the step of deleting a set number of forward warehouses from the initial path through the destruction operator, and repeat the process until the final path is obtained; wherein the importance is determined by the transportation requirements in the order information corresponding to the forward warehouse; and the target value is determined according to the transportation cost of the path.

[0042] In a third aspect, an embodiment of the present application further provides a computing device, comprising: a memory for storing programs; a processor for calling the programs stored in the memory and executing the methods described in the various possible designs of the first aspect according to the obtained programs.

[0043] In a fourth aspect, an embodiment of the present application further provides a computer-readable non-volatile storage medium, comprising a computer-readable program. When a computer reads and executes the computer-readable program, the computer executes the method described in the various possible designs of the first aspect.

[0044] These implementations or other implementations of the present application will be more concise and understandable in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0046] Figure 1 A schematic diagram of the architecture of a transport route planning provided in an embodiment of the present application;

[0047] Figure 2 A schematic diagram of the architecture of a transport route planning provided in an embodiment of the present application;

[0048] Figure 3 A flow chart of a transportation route planning method provided in an embodiment of the present application;

[0049] Figure 4 A trend chart showing the impact of a transportation route planning method on transportation costs provided in an embodiment of the present application;

[0050] Figure 5 A flow chart of a transportation route planning method provided in an embodiment of the present application;

[0051] Figure 6 A schematic diagram of a transport route planning device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] To make the objectives, technical solutions, and advantages of this application more clear, this application will be further described in detail below with reference to the accompanying drawings. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of this application.

[0053] Figure 1The system architecture of a transport route planning service provided in an embodiment of the present application includes a basic data module, a preliminary optimization module, and an optimization module. After receiving multiple order information, the transport route planning system generates an initial route based on the basic data in the basic data module and the preliminary optimization algorithm in the preliminary optimization module. This initial route is then transmitted to the optimization module, which generates a final route output based on the algorithm in the optimization module and the basic data in the basic data module.

[0054] Specifically, the basic data contained in the basic data module may include transportation cost pricing methods, transportation parameters, road network data, vehicle resources, optional activation algorithms and other related basic data.

[0055] The preliminary optimization module is configured to, based on a mileage saving method, determine, based on multiple order information received from a transportation route planning service (the order information includes transportation starting and ending stations and transportation requirements, with the transportation starting and ending stations including a main warehouse as the starting point and a forward warehouse as the ending point), if it is determined that any of the multiple order information has a transportation service demand exceeding a first preset threshold, split the order information exceeding the first preset threshold into at least two order information based on the splitting algorithm in the optional activation algorithm, with the transportation service demand of each split order information being lower than the first preset threshold; or, if it is determined that any of the multiple order information has a transportation service demand lower than a second preset threshold, merge the order information lower than the second preset threshold with one or more other order information into one order information based on the splitting algorithm in the optional activation algorithm, with the transportation service demand of each combined order information being lower than the first preset threshold. In this way, multiple order information is obtained, and at least one temporary route is determined based on the multiple order information. Further, the transportation cost and route accessibility of each temporary route are determined based on the transportation requirements in the multiple order information (the transportation cost and route accessibility of the corresponding temporary route are calculated based on the transportation requirements in the order information and the basic data in the basic data module). Path accessibility is determined based on the distance between each forward warehouse in the path (the distance between the forward warehouses can be determined based on the road network data). The closer the distance between each forward warehouse in the path, the higher the path accessibility. In other words, path accessibility can be understood as the convenience of the transportation path. For example, the transportation distance between forward warehouses is relatively short, and the road conditions between forward warehouses are good during the corresponding transportation period. Afterwards, for each temporary path, the transportation cost and path accessibility of the temporary path are substituted into the objective function to obtain the target value of the temporary path. Determine the temporary path with the lowest target value from at least one temporary path as the initial path, and transmit the initial path to the optimization module.

[0056] The optimization module includes a variety of destruction operators. For example, a first random removal operator for randomly removing the forward warehouse in the initial path, a second random removal operator for randomly removing the sub-path in the initial path, a cost removal operator for removing the forward warehouse with high transportation service demand in the initial path, a path removal operator for randomly removing a part of the path in the sub-path in the initial path, and a time removal operator for removing the forward warehouse with short transportation time requirement in the initial path. It also includes a variety of repair operators. For example, an operator for inserting the forward warehouse removed by the destruction operator, or the removed sub-path, or the part of the removed sub-path into the optimal position of the destruction path, so that the path accessibility of the obtained updated path is maximized. The optimization module selects the destruction operator and the repair operator using a roulette wheel method based on their destruction and repair operators, as well as the destruction operator scores and repair operator scores. A set number of forward bins are removed from the initial path using the selected destruction operator to obtain a destruction path. The importance of the removed forward bins is determined using the selected repair operator. Using the importance as the selection probability, the removed forward bins are sequentially inserted into the optimal positions of the destruction path to obtain an updated path. If the target value of the updated path is not greater than that of the initial path, the updated path is used as the initial path. If the target value of the updated path is greater than that of the initial path, the initial path is not updated. According to the optimization effect of the updated path, the selected destruction operator and repair operator are scored, so that they can be used as a reference for the probability of selecting the destruction operator and repair operator by the roulette wheel method in subsequent optimization. Return to the steps of selecting the destruction operator and repair operator respectively by the roulette wheel method, and repeat the process until the final path is obtained; wherein, the importance is determined by the transportation requirements in the order information corresponding to the forward warehouse; the target value is determined according to the transportation cost of the path. In this way, the forward warehouse deleted by the destruction operator is inserted into the destruction path according to the importance, and the forward warehouse with high transportation requirements is inserted into the path first, so that the path optimization effect is maximized in the path optimization of this cycle (for ease of understanding, if the forward warehouse with relatively low importance is inserted into the optimal position of the destruction path first, the target value of the obtained path will be less optimized, and the forward warehouse with relatively low importance will seize the optimal position of the forward warehouse with relatively high importance, affecting the optimization efficiency.If a more important forward bin is inserted into the optimal position of the destruction path, the resulting path's target value will be optimized to a greater degree. The more important forward bin will seize the optimal position of the less important forward bin, maximizing the optimization effect and significantly improving optimization efficiency. Furthermore, during this path optimization process, the algorithm is optimized using a roulette wheel method and by assigning scores to the destruction and repair operators based on the updated path. This ensures that each cycle of the path optimization algorithm is more efficient than the previous cycle, further improving path optimization efficiency.

[0057] Based on the above transport route planning service, the embodiment of the present application also provides a system architecture for transport route planning, such as Figure 2 As shown, the transport path planning system includes a warehouse management system, a transport management system, and Figure 1 The transport routing service shown in . The transport routing service can be installed in the transport management system to provide a routing optimization function, or the transport management system can implement the routing optimization function by calling a method. There is no specific limitation on how the transport management system provides the routing optimization function through the transport routing service.

[0058] The warehouse management system (WMS) takes the integration of warehouse operation technology as its main goal, making inventory a flow link in the assembly line and the assembly line an integral part of inventory operations. It can generate order information based on the storage attributes and storage needs of warehouses such as forward warehouses and large warehouses, and push the order information to the transportation management system.

[0059] A transportation management system (TMS) is a web-based operating software package within the "supply chain" group of logistics. It improves logistics management capabilities through a variety of methods and other related operations, including managing shipping units, specifying intra-enterprise, domestic, and international shipping plans, managing transportation models, benchmarks, and costs, maintaining transportation data, generating bills of lading, optimizing transportation plans, selecting carriers and service methods, auditing and paying freight bills, handling cargo damage claims, arranging labor and space, managing documents (especially when shipping internationally), and managing third-party logistics, among others. The transportation route planning service in this application can quickly provide staff with a final route with a good optimization effect based on the transportation management system, and the transportation management system can provide basic data for the transportation route planning service.

[0060] Based on the above system architecture, the embodiment of the present application provides a transportation route planning method process, such as Figure 3 Shown, including:

[0061] Step 301: Receive multiple order information, where any order information includes a transportation start and end station and transportation requirements; the transportation start and end stations include a large warehouse as the starting point and a forward warehouse as the end point;

[0062] Step 302: Determine an initial path based on the plurality of order information, where the initial path includes all major warehouses and forward warehouses in the plurality of order information;

[0063] Here, the initial path can be preliminarily optimized. For example, the calculated initial path is the path with the lowest transportation cost corresponding to multiple order information, or the calculated initial path is the path with the highest path accessibility corresponding to multiple order information, or the path with the lowest target value obtained by substituting the transportation cost and path accessibility calculated based on multiple order information into the objective function, etc. The initial path can also be obtained without preliminarily optimizing, and is obtained by randomly permuting the order information. There is no specific restriction on the method for obtaining the initial path.

[0064] Step 303: Delete a set number of forward warehouses from the initial path through the destruction operator to obtain a destroyed path; determine the importance of the deleted forward warehouses through the repair operator, and use the importance as the selection probability to insert the deleted forward warehouses into the optimal position of the destroyed path in sequence to obtain an updated path; if the target value of the updated path is not greater than the target value of the initial path, use the updated path as the initial path, return to the step of deleting a set number of forward warehouses from the initial path through the destruction operator, and repeat the process until the final path is obtained; wherein, the importance is determined by the transportation requirements in the order information corresponding to the forward warehouse; and the target value is determined according to the transportation cost of the path.

[0065] Here, the importance can be determined based on the relevant transportation requirement information such as the individual volume of the goods, the overall volume of the goods, whether they are fresh or not, the manpower required for handling, the loading time, the unloading time, the distance between the forward warehouse and the main warehouse, etc. in the order information corresponding to the forward warehouse. The importance calculation can be obtained by adding up the aforementioned items, or by setting corresponding weights for each item and then calculating the sum. Special items (such as fresh or not corresponds to different coefficient values, and the coefficient values ​​can be determined based on experience or professional knowledge) can also be used as coefficients to calculate the importance of each item. There is no restriction on the specific calculation method of the importance here.

[0066] In one example, the main warehouse is O, and there are 5 forward warehouses with demand, namely a, b, c, d, and e. The initial path is OabOced (OabOced means that the first vehicle starts from the main warehouse O, first serves the forward warehouse a and then serves the forward warehouse b; the second vehicle starts from the main warehouse O, first serves the forward warehouse c, then serves the forward warehouse e, and then serves the forward warehouse d. In this process, the receiving time of each forward warehouse can be input in advance as a transportation requirement, or it can be not required in advance. After the final path is obtained by subsequent calculation, the receiving time of each forward warehouse is given in the final path. Time), the initial path contains two sub-paths Oab and Oced. According to the transportation requirements of each forward warehouse in the two sub-paths, vehicles are assigned to the two sub-paths at the main warehouse O. When necessary, the transportation cost and importance of the forward warehouse in each sub-path can be obtained based on its transportation requirements (the order information corresponding to the forward warehouse may include relevant information such as the type of goods it transports, the amount obtained, the delivery time, etc. Based on this information, the transportation requirements of the forward warehouse can be determined, and then the importance of the forward warehouse, as well as the path and the transportation cost of the forward warehouse) and other information. During the path optimization process, the destruction operator deletes the two forward warehouses a and d to generate a destruction path ObOce. The importance of the two forward warehouses a and d is calculated. If the importance of a is higher than that of d, the importance of the forward warehouse is used as the probability of selecting the forward warehouse, and the forward warehouse is selected through the roulette method or tournament method. In this way, the higher the importance, the greater the probability of the forward warehouse being selected. If forward warehouse a is selected, forward warehouse a is inserted into the optimal position of the destroyed path ObOce through the repair operator (the target values ​​of the transportation cost and path accessibility corresponding to the path OabOce under the objective function are less than the target values ​​of the paths ObaOce, ObOace, ObOcae, and ObOcea) to obtain OabOce. Then, forward warehouse d is inserted into OabOce to obtain the updated path OabOdce (the target values ​​of the transportation cost and path accessibility corresponding to the path OabOdce under the objective function are less than the target values ​​of the paths OdabOce, OadbOce, OabdOce, OabOdce, OabOcde, and OabOced). Afterwards, it is determined whether the target value of the updated path OabOdce is not greater than the target value of the initial path OabOced. If so, the updated path OabOdce is used to update the initial path OabOced and serve as the initial path OabOdce for the next cyclic path optimization. In addition, it should be noted that the method for determining whether to update the initial path OabOced with the updated path OabOdce can be a simulated annealing strategy. It should be noted that this example is only for ease of understanding and does not actually affect the number of large warehouses and forward warehouses (in actual applications, the number of large warehouses and forward warehouses can be very large), the number and type of assigned vehicles (the number of assigned vehicles can be multiple, and corresponding types of vehicles can be assigned according to the types of large warehouses and forward warehouses).For example, if the large warehouse and the forward warehouse are warehouses corresponding to the cold chain, they can be assigned corresponding cold chain vehicle transportation), the transportation cost and importance calculation method of the large warehouse and the forward warehouse, the way the destruction operator destroys the initial path, and the way the repair operator repairs the damaged path are restricted.

[0067] In the above method, multiple order information can be received, and the final path can be determined based on the transportation starting and ending stations and transportation requirements in the multiple order information. In this process, the importance of the forward warehouse is used as a reference factor for initial path optimization. The higher the importance of the forward warehouse, the greater the transportation requirements such as vehicle volume and vehicle cost of the initial path - the greater the transportation cost. Under certain vehicle volume and vehicle cost in the initial path, the forward warehouse with high importance is taken as a relatively priority optimization object, which effectively improves the optimization degree and efficiency. In the application, it can speed up the speed of obtaining the final path and improve the optimization of obtaining the final path.

[0068] In the above step 302, an initial path is determined according to the multiple order information, including: based on the mileage saving method, determining at least one temporary path according to the multiple order information; determining the transportation cost and path accessibility of each temporary path according to the transportation requirements in the multiple order information, the path accessibility is determined according to the distance between each forward warehouse in the path, and the shorter the distance between each forward warehouse in the path, the higher the path accessibility; for each temporary path, substituting the transportation cost and path accessibility of the temporary path into the objective function to obtain the target value of the temporary path; and determining the temporary path with the lowest target value from the at least one temporary path as the initial path.

[0069] In other words, if the destruction and repair operators are directly used to optimize the randomly obtained initial path, the solution space may become extremely large, significantly impacting optimization efficiency. If the final path needs to be obtained within 5 minutes, the optimization effect of the final path may be poor, resulting in significant transportation costs. Therefore, a mileage-saving method can be used to obtain at least one temporary path, ensuring that the mileage of this temporary path is at a relatively optimal solution. Next, the transportation cost (based on the distance from the main warehouse to the forward warehouse, the cities where the main warehouse and forward warehouse are located, the vehicle type assigned to the temporary path, and the mileage pricing of each vehicle type) and path accessibility (based on road network data, such as the distance between the main warehouse and forward warehouse in the temporary path and road conditions) are calculated for each temporary path. The transportation cost and path accessibility of each temporary path are then substituted into the objective function to obtain the target value. The temporary path with the lowest target value among the temporary paths is then selected as the initial path. This reduces the solution space, allowing for faster and more optimal final paths to be obtained in less time when optimizing the initial path using the destruction and repair operators. For ease of understanding, a simple example of the objective function is given here. The objective function is Y=a*1000+b*1, where a is the transportation cost and b is the path accessibility. In this example, the objective function is an integrated function with transportation cost first and path accessibility second. In this example, the sum of the transportation costs of all vehicles in the path can be used as the transportation cost of the path, and the sum of the distances from the large warehouse to the forward warehouse in the path, and the sum of the distances from the forward warehouse to the next forward warehouse can also be used as the path accessibility. It should be noted that there are no restrictions on the examples of the objective function and the calculation of the transportation cost and path accessibility in the objective function. For example, the objective function can be Y=a 2 +b, etc., labor costs can also be added to the transportation costs, and road conditions, the number of red lights on the path, etc. can also be considered in the path accessibility.

[0070] In the method flow of the optimization step 302 of the above-mentioned method flow for transport route planning, the transport cost of each temporary route is determined based on the transport requirements in the plurality of order information, including: for any temporary route, determining the distance between each node in the temporary route based on the road network data; each node includes a main warehouse and a forward warehouse; allocating vehicles based on the transport requirements in each order information; and determining the transport cost of the temporary route based on the unloading time of each forward warehouse in each order information, the mileage pricing of the vehicle type of the allocated vehicle, the city mileage pricing of the city involved, and the distance between each node. In one example, the navigation distance and time-road network data of all point pairs can be obtained by calling the truck navigation of the map software. The receiving time and unloading time of the forward warehouse are determined based on the order information of the forward warehouse. The cost pricing method can be obtained based on the mileage pricing of the vehicle type of the allocated vehicle and the city mileage pricing of the city involved. For example, based on the vehicle type (cold chain), vehicle size (4.2 meters), and the cost calculation method for the cities involved (tiered pricing), the cost is 500 yuan for [0-100 km] and 700 yuan for [100-150 km]. The pricing method can also include labor costs, unloading time costs, and other factors. The transportation cost calculation method and specific application information can be customized based on specific needs and are not limited here.

[0071] In step 303 of the above method flow, the destruction operator includes multiple types; before deleting a set number of forward warehouses from the initial path by the destruction operator, the method further includes:

[0072] In each round of path optimization, the destruction operator used for path optimization is selected using the roulette wheel method;

[0073] After taking the updated path as the initial path, the method further includes:

[0074] After the current round of path optimization is completed, the score of the destruction operator is updated based on the updated path. This score is used to select the probability parameter for the destruction operator in the subsequent roulette wheel method. In other words, the destruction operator in the above-mentioned transportation route planning method process can be applied differently in each cycle. Before each cycle of path optimization, the destruction operator can be optimized, and the score of the destruction operator can be used as the probability parameter for the roulette wheel method to select the destruction operator as the destruction operator for the current cycle of path optimization. After the current cycle of path optimization is completed, the destruction operator is scored based on the degree of optimization of the updated path obtained in this round. The score of the destruction operator can be updated based on the score, and the updated score of the destruction operator can be used as the probability parameter for selecting the destruction operator in the next cycle of path optimization.

[0075] The aforementioned multiple destruction operators may include at least one of a first random removal operator, a second random removal operator, a cost removal operator, a path removal operator, and a time removal operator. The first random removal operator is used to randomly remove forward warehouses from the initial path, the second random removal operator is used to randomly remove subpaths from the initial path, the cost removal operator is used to remove forward warehouses with high transportation service requirements from the initial path, the path removal operator is used to randomly remove portions of subpaths within the initial path, and the time removal operator is used to remove forward warehouses with short transportation time requirements from the initial path. In other words, during the transportation route planning process, the algorithm can optimize the initial path and updated path obtained from multiple order information to select the most appropriate destruction operator for the optimized path. In one example, when the path characteristic is that each forward warehouse has an equal chance of being optimized, the algorithm optimizes the first random removal operator, randomly removing forward warehouses from the initial path with equal probability of removal for each forward warehouse. The repair operator is then used to insert the randomly removed forward warehouses into the optimal position of the destroyed initial path to obtain the updated path. When the path characteristic requires equal opportunity for optimization for each subpath, the algorithm optimizes using the second random removal operator. Subpaths are randomly removed from the initial path with equal probability of removal. The repair operator is then used to insert these randomly removed subpaths into the optimal position of the damaged initial path to obtain an updated path. Alternatively, to improve optimization efficiency, the cost removal operator can be used to preferentially remove forward warehouses with high transportation service demand from the initial path. The repair operator can then be used to insert these removed forward warehouses into the optimal position of the damaged initial path. This allows for the fastest optimization of these forward warehouses, maximizing the optimization of the initial path's transportation cost and path accessibility in the objective function, thereby improving path optimization efficiency. Optimization efficiency can also be improved by selecting partial paths for optimization from the selection of removal objects and subpaths. The path removal operator can be used to randomly remove partial paths from the subpaths of the initial path. The repair operator can then be used to insert these randomly removed partial subpaths into the optimal position of the damaged initial path to obtain an updated path. It is also possible to use factors such as unloading time and receiving time as a reference, and use the time removal operator to remove the forward warehouses with close transportation time requirements in the initial path, and use the repair operator to insert the forward warehouses with close transportation time requirements into the optimal position of the damaged initial path to obtain an updated path. This ensures that the transportation time requirements between adjacent forward warehouses in the obtained updated path are not too concentrated, and can effectively prevent problems such as staff unloading or transportation in a timely manner. It should be noted that the above-mentioned multiple destruction operators are only examples and do not limit the types of destruction operators used in this application. The present application solution can be applied to one or more of them, as well as other destruction operators.For example, the unloading time and receiving time factors can be added to the cost removal operator as a factor to measure the importance, thereby obtaining the cost-time removal operator.

[0076] In step 303 of the above method flow, there are multiple types of repair operators. Before determining the importance of the deleted forward warehouse through the repair operator, the following steps are also included:

[0077] In each round of path optimization, the repair operator used for path optimization is selected using the roulette wheel method;

[0078] After taking the updated path as the initial path, the method further includes:

[0079] After the current round of path optimization is completed, the score of the repair operator is updated based on the updated path. This score is used as a probability parameter for selecting a repair operator in the subsequent roulette wheel method. In other words, the application of the repair operator in the above-mentioned transportation route planning method process can be different in each cycle. Before using the repair operator for path optimization in each cycle, the repair operator can be optimized first. The score of the repair operator is used as the probability parameter for selecting the repair operator in the roulette wheel method, and the repair operator is selected as the repair operator for the current round of path optimization. After the current round of path optimization is completed, the repair operator is scored based on the degree of optimization of the updated path obtained in this round. The score of the destruction operator can be updated based on this score, and the updated score of the repair operator is used as the probability parameter for selecting the repair operator in the next cycle of the path optimization process.

[0080] In the above-mentioned transportation route planning method process, before step 302, when determining the initial route based on the multiple order information, the method further includes: determining that there is order information among the multiple order information whose transportation service demand exceeds a first preset threshold, splitting the order information exceeding the first preset threshold into at least two order information, and the transportation service demand of each order information obtained by splitting is lower than the first preset threshold; or determining that there is order information among the multiple order information whose transportation service demand is lower than a second preset threshold, combining the order information below the second preset threshold with one or more other order information into one order information, and the transportation service demand of the combined order information is lower than the first preset threshold. In other words, in order to ensure the rational allocation of transportation resources, orders with excessive transportation service demands can be split, and orders with excessively low transportation service demands can be combined to ensure better utilization of transportation resources and save transportation costs.

[0081] Based on the above-mentioned method processes, the embodiment of the present application provides a trend diagram of the impact of the transportation path planning method of the present application on transportation costs, such as Figure 4As shown, before using the transportation route planning method of the present application, the average cost per basket and the average cost per piece were relatively high in the first, second, and third weeks. After using the transportation route planning method of the present application, the average cost per basket and the average cost per piece for the cold chain decreased significantly in the fourth to sixth weeks. The average cost per basket and the average cost per piece for the cold chain also decreased significantly in the seventh to 17th weeks. This shows that the transportation route planning method of the present application can effectively reduce transportation costs.

[0082] Based on the above method flow, the embodiment of the present application provides a transportation route planning method flow, such as Figure 5 Shown, including:

[0083] Step 501: Receive multiple order information.

[0084] Step 502: Split and / or combine multiple order information to obtain multiple processed order information.

[0085] Step 503: Calculate at least one temporary route of the processed multiple order information based on the mileage saving method.

[0086] Step 504: Calculate the transportation cost and path accessibility of each temporary path, and substitute the transportation cost and path accessibility of the temporary path into the objective function to obtain the target value corresponding to the temporary path.

[0087] Step 505: The temporary path with the lowest target value among the temporary paths is used as the initial path.

[0088] Step 506: Select a destruction operator for this round of path optimization from multiple destruction operators through a roulette algorithm.

[0089] Step 507: Deleting a set number of forward warehouses from the initial path using a destruction operator to obtain a destruction path.

[0090] Step 508: Calculate the importance of the deleted forward warehouse.

[0091] Step 509: Select a repair operator for this round of path optimization from multiple repair operators using a roulette wheel algorithm.

[0092] Step 510: Using the repair operator, the importance of the deleted predecessor warehouse is used as the selection probability, and the deleted predecessor warehouse is inserted into the optimal position of the damaged path in sequence to obtain an updated path.

[0093] Step 511 : Check whether the target value of the updated path is not greater than the target value of the initial path. If so, execute step 512 ; if not, execute step 513 .

[0094] Step 512: Use the updated path as the initial path.

[0095] Step 513: Do not update the initial path.

[0096] Step 514: Return to step 506 and loop through steps 506 to 512 / 513 until the final path is obtained.

[0097] It should be noted that it is possible to set conditions for loop cessation. For example, there may be loop round limits or loop time limits. The conditions for loop cessation and obtaining the final path are not restricted and can be set as needed. In the above process, steps 502 and / or steps 503-505 may be executed or not. If steps 503-505 are not executed, a path randomly determined based on multiple order information may be used as the initial path. In other words, the above process steps are not unique.

[0098] Based on the same concept, the embodiment of the present application provides a transport path planning device, such as Figure 6 As shown, the device includes:

[0099] The transceiver module 601 is used to receive multiple order information, where any order information includes the transportation starting and ending stations and transportation requirements; the transportation starting and ending stations include the main warehouse as the starting point and the forward warehouse as the end point;

[0100] Processing module 602 is configured to determine an initial path based on the plurality of order information, where the initial path includes all major warehouses and forward warehouses in the plurality of order information;

[0101] The processing module 602 is also used to delete a set number of forward warehouses from the initial path through a destruction operator to obtain a destroyed path; determine the importance of the deleted forward warehouses through a repair operator, and use the importance as the selection probability to insert the deleted forward warehouses into the optimal position of the destroyed path in sequence to obtain an updated path; if the target value of the updated path is not greater than the target value of the initial path, then use the updated path as the initial path, return to the step of deleting a set number of forward warehouses from the initial path through the destruction operator, and loop until the final path is obtained; wherein the importance is determined by the transportation requirements in the order information corresponding to the forward warehouse; and the target value is determined according to the transportation cost of the path.

[0102] Optionally, the processing module 602 is specifically used to determine at least one temporary path based on the multiple order information based on the mileage saving method; determine the transportation cost and path accessibility of each temporary path based on the transportation requirements in the multiple order information, and the path accessibility is determined based on the distance between each forward warehouse in the path, and the shorter the distance between each forward warehouse in the path, the higher the path accessibility; for each temporary path, substitute the transportation cost and path accessibility of the temporary path into the objective function to obtain the target value of the temporary path; and determine the temporary path with the lowest target value from the at least one temporary path as the initial path.

[0103] Optionally, the processing module 602 is specifically used to determine, for any temporary path, the distance between each node in the temporary path based on the road network data; the each node includes a main warehouse and a forward warehouse; allocate vehicles according to the transportation requirements in the each order information; determine the transportation cost of the temporary path based on the unloading time of each forward warehouse in the each order information, the mileage price of the vehicle type of the allocated vehicle, the city mileage price of the cities involved, and the distance between the each node.

[0104] Optionally, the destruction operator includes multiple types; the processing module 602 is also used to select the destruction operator used for path optimization in each round of path optimization process using a roulette wheel method; the processing module 602 is also used to update the score of the destruction operator according to the updated path after the end of this round of path optimization, and the score is used for the probability parameter of the destruction operator selected by the subsequent roulette wheel method.

[0105] Optionally, the destruction operator includes at least one of a first random removal operator, a second random removal operator, a cost removal operator, a path removal operator and a time removal operator; wherein, the first random removal operator is used to randomly remove the forward warehouse in the initial path, the second random removal operator is used to randomly remove the sub-path in the initial path, the cost removal operator is used to remove the forward warehouse with high transportation service demand in the initial path, the path removal operator is used to randomly remove part of the path in the sub-path in the initial path, and the time removal operator is used to remove the forward warehouse with short transportation time requirement in the initial path.

[0106] Optionally, there are multiple types of repair operators, and the processing module 602 is also used to select the repair operator used for path optimization in each round of path optimization process using a roulette wheel method; the processing module 602 is also used to update the score of the repair operator according to the updated path after the end of this round of path optimization, and the score is used for the probability parameter of the subsequent roulette wheel method to select the repair operator.

[0107] Optionally, the processing module 602 is also used to determine whether there is order information among the multiple order information whose transportation service demand exceeds a first preset threshold, split the order information exceeding the first preset threshold into at least two order information, and the transportation service demand of each order information obtained by splitting is lower than the first preset threshold; or determine whether there is order information among the multiple order information whose transportation service demand is lower than a second preset threshold, combine the order information lower than the second preset threshold with one or more other order information into one order information, and the transportation service demand of the combined order information is lower than the first preset threshold.

[0108] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0109] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0110] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0111] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0112] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A transportation route planning method, characterized in that: The method comprises: Receive multiple order information, each order information including transportation starting and ending stations and transportation requirements; the transportation starting and ending stations include a large warehouse as the starting point and a forward warehouse as the end point; the transportation requirements include at least one of the following: the volume of the individual goods in the order information, the total volume of the goods, whether they are refrigerated or non-refrigerated, the manpower required for transportation, the loading time, the unloading time, and the distance between the forward warehouse in the order information and the large warehouse in the order information; Determine an initial path based on the multiple order information, where the initial path includes the major warehouses and forward warehouses in the multiple order information; A set number of forward warehouses are deleted from the initial path by a destruction operator to obtain a destroyed path; the importance of the deleted forward warehouses is determined by a repair operator, and the importance is used as the selection probability to insert the deleted forward warehouses into the optimal position of the destroyed path in sequence to obtain an updated path; if the target value of the updated path is not greater than the target value of the initial path, the updated path is used as the initial path, and the step of deleting a set number of forward warehouses from the initial path by the destruction operator is returned to, and the cycle is repeated until the final path is obtained; wherein the importance is determined by the transportation requirements in the order information corresponding to the forward warehouse, and the importance is used to indicate the optimized order of the deleted forward warehouses; the target value is determined according to the transportation cost of the path.

2. The method according to claim 1, wherein Determining an initial path according to the plurality of order information includes: Determining at least one temporary route based on the plurality of order information based on a mileage saving method; Determining the transportation cost and path accessibility of each temporary path based on the transportation requirements in the plurality of order information, wherein the path accessibility is determined based on the distance between each forward warehouse in the path, and the closer the distance between each forward warehouse in the path, the higher the path accessibility; For each temporary path, the transportation cost and path accessibility of the temporary path are substituted into the objective function to obtain the target value of the temporary path; A temporary path with the lowest target value is determined from the at least one temporary path as the initial path.

3. The method according to claim 2, wherein Determining the transportation cost of each temporary path according to the transportation requirements in the plurality of order information includes: For any temporary path, determine the distance between each node in the temporary path according to the road network data; each node includes a large warehouse and a forward warehouse; Allocate vehicles based on the transportation requirements in each order information; The transportation cost of the temporary path is determined based on the unloading time of each forward warehouse in the order information, the mileage price of the vehicle type of the assigned vehicle, the city mileage price of the city involved, and the distance between the nodes.

4. The method according to claim 1, wherein The destruction operator includes multiple types; before deleting a set number of forward warehouses from the initial path through the destruction operator, it also includes: In each round of path optimization, the destruction operator used for path optimization is selected using the roulette wheel method; After taking the updated path as the initial path, the method further includes: After the current round of path optimization is completed, the score of the destruction operator is updated according to the updated path, and the score is used for the subsequent roulette wheel method to select the probability parameter of the destruction operator.

5. The method according to claim 4, wherein The destruction operator includes at least one of a first random removal operator, a second random removal operator, a cost removal operator, a path removal operator and a time removal operator; wherein the first random removal operator is used to randomly remove the forward warehouse in the initial path, the second random removal operator is used to randomly remove the sub-path in the initial path, the cost removal operator is used to remove the forward warehouse with high transportation service demand in the initial path, the path removal operator is used to randomly remove part of the path in the sub-path in the initial path, and the time removal operator is used to remove the forward warehouse with short transportation time requirement in the initial path.

6. The method according to claim 1, wherein There are many types of repair operators. Before determining the importance of the deleted forward warehouse through the repair operator, it also includes: In each round of path optimization, the repair operator used for path optimization is selected using the roulette wheel method; After taking the updated path as the initial path, the method further includes: After the current round of path optimization is completed, the score of the repair operator is updated according to the updated path, and the score is used for the subsequent roulette wheel method to select the probability parameter of the repair operator.

7. The method according to any one of claims 1 to 6, wherein: Before determining the initial path according to the plurality of order information, the method further includes: Determining that there is order information among the multiple order information whose transportation service demand exceeds a first preset threshold, splitting the order information exceeding the first preset threshold into at least two order information, where the transportation service demand of each of the split order information is lower than the first preset threshold; or Determine that there is order information among the multiple order information whose transportation service demand is lower than a second preset threshold, and combine the order information below the second preset threshold with one or more other order information into one order information, and the transportation service demand of the combined order information is lower than the first preset threshold.

8. A transport path planning device, characterized in that: The device comprises: a transceiver module configured to receive multiple order information, wherein each order information includes a transportation start and end station and transportation requirements; the transportation start and end stations include a main warehouse as the starting point and a forward warehouse as the end point; and the transportation requirements include at least one of the following: the volume of the individual goods in the order information, the total volume of the goods, whether they are refrigerated or non-refrigerated, the manpower required for transportation, the loading time, the unloading time, and the distance between the forward warehouse in the order information and the main warehouse in the order information; A processing module, configured to determine an initial path according to the plurality of order information, wherein the initial path includes all major warehouses and all forward warehouses in the plurality of order information; The processing module is also used to delete a set number of forward warehouses from the initial path through a destruction operator to obtain a destroyed path; determine the importance of the deleted forward warehouses through a repair operator, and use the importance as the selection probability to insert the deleted forward warehouses into the optimal position of the destroyed path in sequence to obtain an updated path; if the target value of the updated path is not greater than the target value of the initial path, then use the updated path as the initial path, return to the step of deleting a set number of forward warehouses from the initial path through the destruction operator, and loop until the final path is obtained; wherein the importance is determined by the transportation requirements in the order information corresponding to the forward warehouse, and the importance is used to indicate the optimization order of the deleted forward warehouses; the target value is determined based on the transportation cost of the path.

9. A computing device, characterized in that include: a memory for storing program instructions; A processor, configured to call the program instructions stored in the memory and execute the method according to any one of claims 1 to 7 according to the obtained program.

10. A computer-readable non-volatile storage medium, characterized in that: The method comprises computer-readable instructions, and when a computer reads and executes the computer-readable instructions, the computer is caused to perform the method according to any one of claims 1 to 7.

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