Delivery planning device, delivery planning method, and delivery planning program
The delivery planning device optimizes multi-trip delivery routes by considering the positional relationship of delivery destinations, enhancing driver efficiency and safety through improved skill development.
Patent Information
- Application Number
- JP2024100763
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2024-06-21
- Publication Date
- 2026-01-08
AI Technical Summary
Existing delivery route planning systems do not consider the accumulation of driver skills, leading to inefficient delivery routes that may decrease driver efficiency and increase the risk of accidents or violations.
A delivery planning device and method that calculates multi-trip delivery plans based on the positional relationship of delivery destinations to improve driver skills by ensuring trips are located closer together, using a processor and memory to optimize delivery routes.
Enhances driver efficiency by improving delivery skills and reducing the likelihood of accidents or violations while maintaining reasonable time and distance efficiency.
Smart Images

Figure 2026002635000001_ABST
Abstract
Description
[Technical Field]
[0001] The present disclosure relates to a delivery planning device, a delivery planning method, and a delivery planning program. [Background technology]
[0002] Conventionally, a computer has been used to plan delivery routes for delivering each package to each destination. For example, Patent Document 1 discloses a method for creating an optimal package delivery plan depending on the road conditions to the destination, thereby reducing the burden on the vehicle driver. [Prior art documents] [Patent documents]
[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-82755 Summary of the Invention [Problem to be solved by the invention]
[0004] The delivery route that takes the shortest time to deliver all packages or the shortest delivery distance is not necessarily the optimal delivery route. For example, if a single driver drives multiple delivery routes in a day and each delivery route is in a different area, the driver's delivery skills will not be accumulated, and delivery efficiency may actually decrease.
[0005] An object of the present disclosure is to provide a technology for planning a delivery route that takes into account the accumulation of delivery skills of a driver. [Means for solving the problem]
[0006] One aspect of the present disclosure provides a delivery planning device that creates a delivery plan, the delivery planning device comprising a processor and memory, wherein the processor works in cooperation with the memory to calculate costs related to a multi-trip that includes multiple trips that start from a base, visit at least one delivery destination, and return to the base, based on the relationships between the multiple trips included in the multi-trip.
[0007] One aspect of the present disclosure provides a delivery planning method for creating a delivery plan using a computer, which calculates costs for a multi-trip that includes multiple trips that start from a base, visit at least one delivery destination, and return to the base, based on the relationships between the multiple trips included in the multi-trip.
[0008] One aspect of the present disclosure provides a delivery planning program that creates a delivery plan and causes a computer to calculate costs related to a multi-trip that includes multiple trips that start from a base, visit at least one delivery destination, and return to the base, based on the relationships between the multiple trips included in the multi-trip.
[0009] These comprehensive or specific aspects may be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or a recording medium, or may be realized as any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium. [Effects of the Invention]
[0010] According to the present disclosure, delivery routes can be planned taking into account the driver's accumulated delivery skills. [Brief explanation of the drawings]
[0011] [Figure 1] A block diagram showing a configuration example of a delivery planning device according to a first embodiment. [Figure 2] Table showing an example of a vehicle information DB according to the first embodiment [Figure 3]Table showing an example of a package information DB according to the first embodiment [Figure 4] FIG. 1 is a diagram showing an example of a distance matrix DB according to the first embodiment; [Figure 5] 1 is a flowchart showing an example of overall processing executed by the delivery planning device according to the first embodiment. [Figure 6] 1 is a flowchart showing an example of a delivery plan creation process according to the first embodiment. [Figure 7] FIG. 1 is a diagram for explaining a method for creating a multi-trip initial solution according to the first embodiment. [Figure 8A] FIG. 1 is a diagram for explaining transfer between multi-trips according to the first embodiment. [Figure 8B] FIG. 1 is a diagram for explaining exchange between multi-trips according to the first embodiment. [Figure 9] 1 is a flowchart showing an example of a process for calculating inter-trip proximity costs based on the proximity of distances between trips according to the first embodiment; [Figure 10] FIG. 1 is a diagram for explaining a first calculation method of single trip center coordinates according to the first embodiment; [Figure 11] FIG. 10 is a diagram for explaining a second calculation method of single trip center coordinates according to the first embodiment; [Figure 12] FIG. 10 is a diagram for explaining a third calculation method of single trip center coordinates according to the first embodiment; [Figure 13] FIG. 1 is a diagram for explaining a method for calculating total trip center coordinates according to the first embodiment. [Figure 14] 1 is a flowchart showing an example of a process for calculating inter-trip proximity costs based on directional proximity between trips according to the first embodiment; [Figure 15] FIG. 10 is a diagram for explaining a method for calculating angles formed by lines connecting a base point and each single trip center coordinate according to the first embodiment; [Figure 16] FIG. 10 is a diagram showing an example of displaying an area and a delivery destination according to the first embodiment. [Figure 17] FIG. 1 is a diagram showing first and second multi-trips before modification as a first example according to the first embodiment; [Figure 18]FIG. 1 is a diagram showing first and second multi-trips after modification as a first example according to the first embodiment; [Figure 19] FIG. 10 is a diagram showing first and second multi-trips before modification as a second example according to the first embodiment; [Figure 20] FIG. 10 is a diagram showing an example of first and second multi-trips after modification as a second example according to the first embodiment; [Figure 21] FIG. 10 is a diagram showing first and second multi-trips before modification as a third example according to the first embodiment; [Figure 22] FIG. 10 is a diagram showing an example of first and second multi-trips after change as a third example according to the first embodiment; DETAILED DESCRIPTION OF THE INVENTION
[0012] Hereinafter, embodiments of the present disclosure will be described in detail with appropriate reference to the drawings. However, more detailed description than necessary may be omitted. For example, detailed descriptions of already well-known matters and redundant descriptions of substantially identical configurations may be omitted. This is to avoid unnecessary redundancy in the following description and to facilitate understanding by those skilled in the art. Note that the accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure and are not intended to limit the subject matter described in the claims. Furthermore, the function of one configuration shown in the present embodiment may be realized by two or more physical configurations, or the functions of two or more configurations may be realized by, for example, one physical configuration.
[0013] (Embodiment 1) <Background to disclosure> A single vehicle (with a single driver) loads cargo at a warehouse (base), travels to multiple delivery destinations, delivers the cargo, and returns to the warehouse (base). This is called a trip. A single vehicle (with a single driver) may also make multiple trips like this. This is called a multi-trip.
[0014] Conventionally, multi-trip delivery plans are created by considering only distance or time efficiency, without considering the relative locations of each trip.
[0015] However, if the trips are located far apart, the driver will deliver to different areas on the same day, making it difficult to improve the driver's delivery skills, such as selecting safe roads, selecting appropriate parking spots, and selecting appropriate locations to store packages. In other words, if the locations of multiple trips are closer together, the driver's delivery skills will improve, and even if distance or time efficiency deteriorates somewhat, the driver will be less likely to have an accident or commit a violation, and the value of customer service will improve.
[0016] Therefore, in this embodiment, a technique for creating a delivery plan that takes into account the positional relationship of multi-trips will be described.
[0017] <Configuration> FIG. 1 is a block diagram showing an example of the configuration of a delivery planning device 1 according to the first embodiment.
[0018] The delivery planning device 1 is a device that creates a delivery plan that takes into account the positional relationship of a multi-trip. The delivery planning device 1 includes a processor 11, a memory 12, a storage 13, and a communication unit 14. The delivery planning device 1 may also be interpreted as an information processing device, a computer, or a server.
[0019] The processor 11 realizes the functions of the delivery planning device 1 by reading and executing predetermined programs and data from the memory 12. For example, the processor 11 realizes the functions of a delivery plan creation unit 21, a cost calculation unit 22, and a distance matrix generation unit 23. Details of these functions will be explained as appropriate. The processor 11 is configured using, for example, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a DSP (Digital Signal Processor), or an FPGA (Field-Programmable Gate Array). The processor 11 may also include a GPU (Graphics Processing Unit) and / or an NPU (Neural Processing Unit).
[0020] The memory 12 is configured by a volatile storage medium and / or a non-volatile storage medium, and stores programs and data.
[0021] The storage 13 is configured with a nonvolatile storage medium (for example, a flash memory, a solid state drive (SSD), or a hard disk drive (HDD)) and stores programs and data. The storage 13 also stores an area information DB 31, a cargo information DB 32, a vehicle information DB 33, and a distance matrix DB 34. Details of these DBs will be described later.
[0022] The communication unit 14 transmits and receives information to and from, for example, the user terminal 2 via the communication network 3. The communication network 3 is, for example, the Internet, a wired LAN, a wireless LAN, or a mobile communication network.
[0023] In response to a user operation, the user terminal 2 transmits a request to create a delivery plan to the delivery planning device 1, and receives and displays the delivery plan created by the delivery planning device 1. Examples of the user terminal 2 include a PC, a tablet terminal, a smartphone, etc.
[0024] FIG. 2 is a table showing an example of the vehicle information DB 33 according to the first embodiment.
[0025] As shown in Fig. 2, the vehicle information DB 33 manages vehicle information as a database. The vehicle information includes items such as a vehicle identification for identifying the vehicle and a maximum load capacity of the vehicle. For example, the vehicle information in the first row of the table shown in Fig. 2 indicates that the maximum load capacity of "Vehicle A" (vehicle identification) is "4".
[0026] FIG. 3 is a table showing an example of the package information DB 32 according to the first embodiment.
[0027] As shown in Fig. 3, the package information DB32 manages package information as a database. Package information includes items such as package identification, location (latitude, longitude), package weight, and delivery time specification. For example, the package information in the second row of the table shown in Fig. 3 indicates that "Package 1" (package identification) is to be delivered to a destination of (latitude 35, longitude 134), the package weight is "0.1", and the specified delivery time is between "8:00 and 12:00".
[0028] FIG. 4 is a diagram showing an example of the distance matrix DB 34 according to the first embodiment.
[0029] The distance matrix generation unit 23 generates a distance matrix such as that shown in Fig. 4, and registers it in the distance matrix DB 34. The distance matrix shown in Fig. 4 is a table showing the distances between the base (starting point) S and each of the delivery destinations D1 to D8. For example, in the distance matrix shown in Fig. 4, "10" written in the field where row D1 and column D2 intersect indicates that the distance between delivery destinations D1 and D2 is "10". Note that "*" written in the table indicates an arbitrary value.
[0030] <Overall flow> FIG. 5 is a flowchart showing an example of the overall process executed by the delivery planning device 1 according to the first embodiment.
[0031] The delivery plan creation unit 21 receives, for example, vehicle information and cargo information to be used in a delivery plan input by a user from the user terminal 2 (S11). The vehicle information and cargo information may be input directly to the delivery planning device 1 or may be stored in advance in the storage 13 of the delivery planning device 1.
[0032] The delivery plan creation unit 21 executes a delivery plan creation process based on the received vehicle information and package information (S12). Details of the delivery plan creation process will be described later (see FIG. 6).
[0033] The delivery plan creation unit 21 transmits the delivery plan created in step S12 to the user terminal 2. The user terminal 2 displays the received delivery plan (S13), and then this process ends.
[0034] <Delivery plan creation process flow> 6 is a flowchart showing an example of a delivery plan creation process according to Embodiment 1. The process shown in FIG. 6 corresponds to details of step S12 in FIG.
[0035] The delivery plan creation unit 21 creates a multi-trip of an initial solution (S101). Details of how to create the multi-trip of the initial solution will be described later (see FIG. 7).
[0036] The delivery plan creation unit 21 starts processing for transferring packages between the first multi-trip and the second multi-trip (that is, transferring delivery destinations) (S102).
[0037] The delivery plan creation unit 21 determines the cargo to be transferred between the first multi-trip and the second multi-trip (i.e., the delivery destination to be transferred) (S103). Details of the transfer will be described later (see FIG. 8).
[0038] The cost calculation unit 22 calculates the sum of the inter-trip neighborhood cost of the first multi-trip before the transfer and the inter-trip neighborhood cost of the second multi-trip before the transfer (hereinafter referred to as the total cost value before the transfer). The cost calculation unit 22 also calculates the sum of the inter-trip neighborhood cost of the first multi-trip after the transfer and the inter-trip neighborhood cost of the second multi-trip after the transfer (hereinafter referred to as the total cost value after the transfer) (S104). In the following description, the inter-trip neighborhood cost of a multi-trip may be simply referred to as the "cost of the multi-trip." A method for calculating the inter-trip neighborhood cost will be described later (see implementation means 1 and 2).
[0039] The delivery plan creation unit 21 determines whether the total cost value after the transfer is smaller than the total cost value before the transfer (that is, whether the cost has been reduced by the transfer) (S105).
[0040] If the total cost value after the transfer is smaller than the total cost value before the transfer (S105: YES), the delivery plan creation unit 21 sets the first and second multi-trips after the transfer as the current solution (i.e., the first and second multi-trips before the transfer) (S106), and returns the processing to step S103.
[0041] If the total cost value after the transfer is not smaller than the total cost value before the transfer (S105: NO), the delivery plan creation unit 21 determines whether the transferred cargo determined in step S103 is the last transferred cargo (S107).
[0042] If it is not the last transferred package (S107: NO), the delivery plan creation unit 21 returns the process to step S103.
[0043] If it is the last transferred package (S107: YES), the delivery plan creation unit 21 ends the transfer process (S108).
[0044] Next, the delivery plan creation unit 21 performs processing for exchanging packages between multiple trips (i.e., exchanging delivery destinations) (S109). The processing for exchanging packages can be performed by replacing "transfer" shown in FIG. 6 with "exchange," so a description thereof will be omitted here. Details of the exchange will be described later (see FIG. 8).
[0045] Through the above processing, the delivery planning device 1 can determine a multi-trip solution that is likely to have the smallest total cost value. Note that the above processing only evaluates the costs of patterns that can be generated by repeating the transfer and / or replacement processing from the initial solution, so the solution with the smallest total cost value is not necessarily output. However, while evaluating the multi-trip costs of all patterns requires unrealistic calculation time, the cost of the resulting solution is not significantly different from the cost of the solution obtained by the above processing. For this reason, this embodiment uses a configuration that adopts the solution obtained by the above processing so that a solution can be obtained in a realistic time.
[0046] <How to create an initial solution> FIG. 7 is a diagram for explaining a method for creating a multi-trip initial solution according to the first embodiment.
[0047] The delivery plan creation unit 21 creates the first trip T0, for example, randomly.
[0048] Next, the delivery plan creation unit 21 selects one delivery destination D4 to be included in the second trip. For example, the delivery plan creation unit 21 selects the delivery destination D4 that is closest in a straight line to the center coordinate P of the coordinates of the delivery destinations D1 to D3 included in the first trip T0. Then, the delivery plan creation unit 21 creates the second trip so as to include the selected delivery destination D4.
[0049] For the third and subsequent trips, the delivery plan creation unit 21 may select the delivery destination that is closest in a straight line to the center coordinates of each delivery destination included in the trips created before, and create the trips in the same manner as described above.
[0050] The above-described method for creating the initial solution multi-trip is merely an example, and the initial solution multi-trip may be created by any method (for example, randomly). This is because, once the process of FIG. 6 is performed, a solution with almost no difference in practical effectiveness is obtained regardless of the initial solution. In the process of FIG. 6, the loop of steps S102 to S107 is repeated to transfer and / or replace the destinations included in each multi-trip, and evaluate whether the cost has been improved. The result at the point when it is determined that there is little prospect of further improvement is output as the multi-trip solution. Therefore, even if the initial solution is different, the cost of the multi-trip solution obtained after transfer and / or replacement is likely to be equivalent. Note that the process of FIG. 6 only evaluates the costs of patterns that can be generated by repeating the transfer and / or replacement process from the initial solution. Therefore, the candidate multi-trip solutions generated for each initial solution may differ, and as a result, the final multi-trip solution may also differ. However, as described above, the cost of the final solution is not significantly different from the minimum cost among all multi-trip patterns. Therefore, even if the final multi-top solution differs depending on the initial solution, the difference in cost due to the difference in solution is so small that it can be ignored in practice.
[0051] <Transfer> Fig. 8A is a diagram for explaining the transfer between multi-trips according to Embodiment 1. A method of transfer between multi-trips will be described with reference to Fig. 8A.
[0052] For example, as shown in Figure 8A, assume that a first multi-trip includes delivery destinations D1 to D4, and a second multi-trip includes delivery destinations D5 to D8. Here, for example, the first multi-trip is modified to include delivery destination D2 in the second multi-trip, and delivery destination D2 is deleted from the first multi-trip. This is called a "transfer." As a result, the first multi-trip after the transfer will include delivery destinations D1, D3, and D4, and the second multi-trip after the transfer will include delivery destinations D5, D6, D2, D7, and D8.
[0053] For example, if the sum of the cost of the first multi-trip after the transfer and the cost of the second multi-trip after the transfer (i.e., the total cost after the transfer) is smaller than the sum of the cost of the first multi-trip before the transfer and the cost of the second multi-trip before the transfer (i.e., the total cost before the transfer), it can be determined that the total cost has been reduced by the transfer between multi-trips.
[0054] <Exchange> Fig. 8B is a diagram for explaining exchange between multi-trips according to Embodiment 1. A method of exchanging between multi-trips will be described with reference to Fig. 8B.
[0055] For example, as shown in Figure 8B, assume that the first multi-trip includes destinations D1 to D4, and the second multi-trip includes destinations D5 to D8. Here, for example, destination D2 of the first multi-trip is transferred to the second multi-trip, and destination D6 of the second multi-trip is changed to be transferred to the first multi-trip. This is called an "exchange." As a result, after the exchange, the first multi-trip will include destinations D1, D6, D3, and D4, and the second multi-trip will include destinations D5, D2, D7, and D8.
[0056] For example, if the sum of the cost of the first multi-trip after replacement and the cost of the second multi-trip after replacement (i.e., the total cost after replacement) is smaller than the sum of the cost of the first multi-trip before replacement and the cost of the second multi-trip before replacement (i.e., the total cost after replacement), it can be determined that the total cost has been reduced by exchanging multi-trips.
[0057] <Method 1> The calculation method of inter-trip proximity costs by implementation means 1 will be explained. Implementation means 1 creates a delivery plan so that the location relationships of each trip are as close as possible to each other in a multi-trip. This allows the driver to deliver to nearby areas when making multiple trips in one day, improving their delivery skills.
[0058] <Calculation of inter-trip proximity costs based on distance> 9 is a flowchart showing an example of a process for calculating inter-trip proximity costs based on the proximity of the distance between trips according to Embodiment 1. This process may be executed in step S104 of FIG.
[0059] The cost calculation unit 22 calculates the single trip center coordinates P for each trip (S301). For example, the cost calculation unit 22 calculates the single trip center coordinates P by one of the first to third calculation methods described later with reference to FIGS. 10 to 12.
[0060] The cost calculation unit 22 calculates the total trip center coordinates using the single trip center coordinates calculated in step S301 (S302). Details of the total trip center coordinates will be described later (see FIG. 13).
[0061] The cost calculation unit 22 calculates the inter-trip proximity distance based on the distance between the total trip center coordinate and each single trip center coordinate (S303). Note that the method for calculating the inter-trip proximity distance will be described in detail later (see FIG. 13).
[0062] The cost calculation unit 22 calculates the inter-trip neighborhood cost based on the inter-trip neighborhood distance calculated in step S303 and a predetermined cost coefficient (S304). Here, the cost coefficient is a constant used to normalize the inter-trip neighborhood cost to a numerical value of an easy-to-handle size. The cost coefficient basically needs to be a constant value, but multiple cost coefficients may be used based on some conditions. Furthermore, if normalization is not necessary, the cost coefficient may be omitted. For example, the cost calculation unit calculates the inter-trip neighborhood cost using the following (Equation 1).
[0063] Inter-trip neighborhood cost = Inter-trip neighborhood distance × cost coefficient ... (Equation 1)
[0064] Then, the cost calculation unit 22 ends this process.
[0065] Through the above processing, the inter-trip neighborhood cost described in step S104 of FIG. 6 is calculated.
[0066] In step S105 shown in FIG. 6, the delivery plan creation unit 21 compares the total value of the inter-trip neighborhood costs calculated using the above-described method in the state of the first and second multi-trips before the transfer and / or replacement with the total value of the inter-trip neighborhood costs calculated using the above-described method in the state of the first and second multi-trips after the transfer and / or replacement, and determines whether the total cost value of the multi-trips after the transfer and / or replacement has become smaller.
[0067] FIG. 10 is a diagram for explaining a first calculation method of single trip central coordinates according to the first embodiment.
[0068] As shown in FIG. 10, in the first calculation method, the average coordinate (center coordinate) of the coordinates (latitude and longitude) of each delivery destination D1, D2, and D3 included in one trip T1 is calculated and set as the single trip center coordinate P.
[0069] FIG. 11 is a diagram for explaining a second method for calculating single trip central coordinates according to the first embodiment.
[0070] As shown in Figure 11, in the second calculation method, the average coordinate (center coordinate) of the coordinates of each delivery destination D1, D2, D3 included in one trip T1 and the coordinates of the base point (starting point) S is calculated and set as the single trip center coordinate P.
[0071] FIG. 12 is a diagram for explaining a third method for calculating single trip central coordinates according to the first embodiment.
[0072] As shown in Figure 12, in the third calculation method, the average coordinates (center coordinates) of each delivery destination D1, D2, D3 included in one trip T1, the coordinates of the base (starting point) S, and the coordinates of the destination point E (for example, a warehouse where the vehicle returns after completing all deliveries) are calculated, and this is set as the single trip center coordinate P.
[0073] FIG. 13 is a diagram for explaining a method of calculating total trip center coordinates according to the first embodiment.
[0074] As shown in Fig. 13, the average coordinate of multiple single trip center coordinates P1, P2, and P3 corresponding to multiple trips T1, T2, and T3, respectively, is defined as the total trip center coordinate Q. For example, as shown in Fig. 13, if single trip center coordinates P1, P2, and P3 exist, the coordinate of (P1+P2+P3) / 3 is defined as the total trip center coordinate Q.
[0075] In the example of Figure 13, the processing in step S303 calculates the average distance (L1 + L2 + L3) / 3 of the distance L1 between the total trip center coordinate Q and the single trip center coordinate P1, the distance L2 between the total trip center coordinate Q and the single trip center coordinate P2, and the distance L3 between the total trip center coordinate Q and the single trip center coordinate P3, and sets this as the inter-trip proximity distance.
[0076] <Calculation of inter-trip proximity costs based on directional proximity> 14 is a flowchart showing an example of a process for calculating inter-trip proximity costs based on directional proximity between trips according to Embodiment 1. This process may be executed in step S104 of FIG.
[0077] The cost calculation unit 22 calculates the single trip center coordinates for each trip (S401). For example, the cost calculation unit 22 calculates the single trip center coordinates by any one of the first to third calculation methods described above with reference to FIGS. 10 to 12.
[0078] The cost calculation unit 22 calculates the angle formed by the lines connecting the base and each single trip center coordinate (S402). Note that the method for calculating the angle will be described in detail later (see FIG. 15).
[0079] The cost calculation unit 22 identifies the maximum angle among the angles calculated in step S402 (S403). Note that the method for identifying the maximum angle will be described in detail later (see FIG. 15).
[0080] The cost calculation unit 22 calculates the inter-trip neighborhood cost based on the maximum angle identified in step S403 and a predetermined cost coefficient (S404). For example, the cost calculation unit 22 calculates the inter-trip neighborhood cost by the following (Equation 2).
[0081] Inter-trip proximity cost = maximum angle × cost coefficient (Equation 2)
[0082] Then, the cost calculation unit 22 ends this process.
[0083] Through the above processing, the inter-trip neighborhood cost described in step S104 of FIG. 6 is calculated.
[0084] In step S105 shown in FIG. 6, the delivery plan creation unit 21 compares the total value of the inter-trip neighborhood costs calculated using the above-described method in the state of the first and second multi-trips before the transfer and / or replacement with the total value of the inter-trip neighborhood costs calculated using the above-described method in the state of the first and second multi-trips after the transfer and / or replacement, and determines whether the total cost value of the multi-trips after the transfer and / or replacement has become smaller.
[0085] The cost calculation unit 22 may calculate the inter-trip neighborhood costs of each of the first and second multi-trips described in step S104 of FIG. 6 using either the method described in FIG. 9 or the method described in FIG. 14.
[0086] In addition, the cost calculation unit 22 may determine the cost of the multi-trip to be the sum of the cost of the multi-trip calculated using the method described in Figure 9 and the cost of the multi-trip calculated using the method described in Figure 14.
[0087] Furthermore, the cost calculation unit 22 may combine the inter-trip proximity cost with other costs (e.g., distance cost, time cost) to determine the total cost of the multi-trip. For example, the cost calculation unit 22 may calculate the total cost of the multi-trip using the following (Equation 3).
[0088] Total cost of a multi-trip = distance cost of each trip included in the multi-trip × distance cost coefficient + time cost of each trip included in the multi-trip × time cost coefficient + inter-trip proximity cost × cost coefficient ... (Equation 3)
[0089] FIG. 15 is a diagram illustrating a method for calculating angles formed by lines connecting a base and each single trip central coordinate, according to the first embodiment.
[0090] In this case, the cost to be prioritized may be adjusted by the value of the cost coefficient. When the total cost is calculated as the weighted sum of each cost as in (Equation 3), the cost coefficient by which each cost is multiplied corresponds to the weight of each cost. In this case, the cost coefficient indicates the weight of each cost, so each value may be different.
[0091] As shown in FIG. 15, first, the cost calculation unit 22 calculates straight lines M1, M2, and M3 connecting the base S with the respective single trip center coordinates P4, P5, and P6.
[0092] Next, in step S402, the cost calculation unit 22 calculates the angle formed by the lines M1, M2, and M3, that is, the angle θ between the lines M1 and M2. 12 , the angle θ between the lines M2 and M3 23 , the angle θ between the lines M3 and M1 31 Calculate.
[0093] Next, in step S403, the cost calculation unit 22 calculates these angles θ 12 , θ 23 , θ31, the maximum angle θ 31 Identify.
[0094] <Modification of Implementation Means 1> In the first implementation, the cost of a multi-trip is calculated based on the proximity of the distance or direction of the multiple trips included in the multi-trip. However, the cost of a multi-trip may be calculated based on other relationships between the multiple trips. For example, the cost of a multi-trip may be calculated by integrating both the proximity of the distance and the proximity of the direction.
[0095] Furthermore, in the implementation method 1, the average coordinate calculated for multiple coordinates including at least the coordinates of the delivery destinations included in each trip is used as the central coordinate of each trip to evaluate the distance or directional proximity between trips and calculate the cost. However, the coordinates used for this evaluation and cost calculation may be coordinates other than the average coordinates as long as they are determined based on the coordinates of the delivery destinations included in the trip (single-trip representative coordinates). For example, the median of multiple coordinates including the coordinates of the delivery destinations included in the trip may be the single-trip representative coordinate, or the coordinate of the delivery destination farthest or closest from the base S may be the single-trip representative coordinate. Furthermore, the coordinate of the delivery destination with the largest angle or the smallest angle from the base S may be the single-trip representative coordinate. Similarly, the total trip central coordinate does not have to be the average coordinate of each trip constituting a multi-trip. In other words, as long as the coordinates are determined based on the representative coordinates of each trip (total trip representative coordinates), they may be coordinates determined by a calculation method other than calculating the average. Specifically, the total trip representative coordinates may be the median of the representative coordinates of each trip, or a weighted average calculated by weighting each trip according to some condition.
[0096] Furthermore, in implementation method 1, the directional proximity between trips is evaluated using the central coordinates of each trip. However, the directional proximity between trips may also be evaluated without using the central coordinates of each trip. For example, an angle that somehow reflects the angles of the delivery destinations included in each trip may be used as a representative angle to evaluate the directional proximity. Examples of the representative angle include the average or median, or the minimum or maximum, of the angles of the lines connecting base S to the coordinates of each delivery destination.
[0097] <Method 2> The method of calculating the inter-trip proximity cost by implementation means 2 will be described.
[0098] In implementation method 2, delivery areas are set in advance, and a delivery plan is created taking into consideration which area each delivery destination belongs to. For example, a delivery plan is created so that multiple trips include as many delivery destinations as possible that belong to the same area. This allows the driver to deliver to similar areas when making multiple trips in one day, improving their delivery skills. Note that areas may be set in any way, such as by country, prefecture, city, town, or village, or by direction from a base.
[0099] <Area settings> FIG. 16 is a diagram showing an example of displaying areas and delivery destinations according to the first embodiment.
[0100] The user can set an area for the delivery destination. The set area is registered as area information in the area information DB 31. As described above, the area information DB 31 may previously store area information indicating a country, prefecture, city, town, or village, a direction from a base, etc. The area information DB 31 may also previously store coordinates indicating the base and the delivery destination.
[0101] As shown in FIG. 16, the delivery planning device 1 generates and displays a map 200 that allows the user to easily recognize to which area each delivery destination belongs.
[0102] For example, as shown in Fig. 16, the delivery planning device 1 displays a map 200 in which delivery destinations belonging to the same area are drawn in the same style and delivery destinations belonging to different areas are drawn in different styles. More specifically, Fig. 16 shows an example in which delivery destinations belonging to the same area are drawn in the same color or pattern and delivery destinations belonging to different areas are drawn in different colors or patterns. However, delivery destinations belonging to each area may be displayed in a style other than the color or pattern to distinguish them from one another, such as by displaying delivery destinations belonging to the same area with marks of the same shape and delivery destinations belonging to different areas with marks of different shapes.
[0103] For example, the delivery planning device 1 may display a map 200 on which area boundaries 201 are drawn, as shown in FIG.
[0104] For example, as shown in Fig. 16, the delivery planning device 1 may display on the map 200 trips T1 and T2 drawn in a manner corresponding to the areas to which the routes of delivery destinations belong. For example, Fig. 16 displays trips T1 and T2 drawn in colors corresponding to the areas to which routes of different delivery destinations belong. In this case, the smaller the inter-trip proximity cost, the more monochromatic the route. Note that each trip may be displayed separately for each area to which the route of delivery destinations belongs, using other manners, such as changing the thickness of the line indicating the route for each area to which the route of delivery destinations belongs, or using different types of lines such as solid lines and dashed lines.
[0105] <Calculation of inter-trip proximity costs taking area into account> Next, a method for calculating inter-trip proximity costs taking area into consideration will be described.
[0106] The cost calculation unit 22 calculates the inter-trip neighborhood cost of the multi-trip based on the maximum number of delivery destinations in the same area included in the multi-trip and a predetermined cost coefficient.
[0107] For example, the cost calculation unit 22 calculates the inter-trip neighborhood cost of a multi-trip using the following (Equation 4).
[0108] Inter-trip proximity cost = (1 / maximum number of destinations in the same area included in the multi-trip) x cost coefficient ... (Equation 4)
[0109] Alternatively, the cost calculation unit 22 calculates the inter-trip neighborhood cost of a multi-trip using the following (Equation 5).
[0110] Inter-trip proximity cost = number of areas included in multi-trip × cost coefficient ... (Equation 5)
[0111] The cost calculation unit 22 may calculate the inter-trip neighborhood cost using either Equation 4 or Equation 5. Because each area includes one or more delivery destinations, Equation 4, which calculates the inter-trip neighborhood cost based on the number of delivery destinations, is more susceptible to cost changes due to transfer and / or replacement than Equation 5, which calculates the inter-trip neighborhood cost based on the number of areas. Therefore, while using Equation 4 can provide a more precise solution, it is considered that it takes longer to obtain the solution.
[0112] In step S105 shown in FIG. 6, the delivery plan creation unit 21 compares the total value of the inter-trip neighborhood costs calculated by the above-described method in the first and second multi-trip states before the transfer and / or replacement with the total value of the inter-trip neighborhood costs calculated by the above-described method in the first and second multi-trip states after the transfer and / or replacement, and determines whether the inter-trip neighborhood costs after the transfer and / or replacement have decreased.
[0113] Fig. 17 is a diagram showing first and second multi-trips before a change as a first example according to embodiment 1. Fig. 18 is a diagram showing first and second multi-trips after a change as a first example according to embodiment 1. Note that "change" here means to include the above-mentioned "transfer" and / or "exchange."
[0114] As shown in FIG. 17, the first multi-trip 101A before the change has the most delivery destinations in area A, which is "4," and the second multi-trip 102A before the change has the most delivery destinations in area B, which is "3."
[0115] Therefore, according to Equation 4, the total cost value of the first and second multi-trips before the change is (1 / 4 + 1 / 3) = 7 / 12. Note that for ease of explanation, cost coefficients have been omitted, and this also applies hereinafter.
[0116] As shown in FIG. 18, the first multi-trip 101B after the change has the most delivery destinations in area A, which is "3," and the second multi-trip 102B after the change has the most delivery destinations in area B, which is "4."
[0117] Therefore, according to Equation 4, the total cost value of the first and second multi-trips after the change is (1 / 4+1 / 4)=6 / 12.
[0118] When comparing the total cost value before the change (7 / 12) with the total cost value after the change (6 / 12), the total cost value after the change is smaller, so it is determined that the first and second multi-trips after the change can reduce costs more.
[0119] Alternatively, as shown in FIG. 17, the number of areas included in the first multi-trip 101A before the change is "2" (areas A and B), and the number of areas included in the second multi-trip 102A before the change is "1" (area B).
[0120] Therefore, according to Equation 5, the total cost value of the first and second multi-trips before the change is 2+1=3.
[0121] As shown in FIG. 18, the number of areas included in the first multi-trip 101B after the change is "2" (areas A and B), and the number of areas included in the second multi-trip 102B after the change is "1" (area B).
[0122] Therefore, according to Equation 5, the total cost value of the first and second multi-trips before the change is 2+1=3.
[0123] When the total cost value (3) before the change is compared with the total cost value (3) after the change, the cost before the change is the same as the cost after the change, so it is determined that the change will not reduce the cost.
[0124] Fig. 19 is a diagram showing first and second multi-trips before change as a second example according to embodiment 1. Fig. 20 is a diagram showing first and second multi-trips after change as a second example according to embodiment 1.
[0125] As shown in Figure 19, the first multi-trip 101A before the change has the most delivery destinations in area A, which is "4", and the second multi-trip 102A before the change has the most delivery destinations in area B or area C, which is "3".
[0126] Therefore, according to Equation 4, the total cost value of the first and second multi-trips before the change is (1 / 4+1 / 3)=7 / 12.
[0127] As shown in FIG. 20, the first multi-trip 101B after the change has the most delivery destinations in area A, which is "4," and the second multi-trip 102B after the change has the most delivery destinations in area B, which is "3."
[0128] Therefore, according to Equation 4, the total cost value of the first and second multi-trips after the change is (1 / 4+1 / 3)=7 / 12.
[0129] When comparing the total cost value before the change (7 / 12) with the total cost value after the change (7 / 12), the total cost value before the change and the total cost value after the change are the same, so it is determined that the change will not reduce the cost.
[0130] Alternatively, as shown in FIG. 19, the number of areas included in the first multi-trip 101A before the change is "2" (areas A and B), and the number of areas included in the second multi-trip 102A before the change is "2" (area B and area C).
[0131] Therefore, according to Equation 5, the total cost value of the first and second multi-trips before the change is 2+2=4.
[0132] As shown in FIG. 20, the number of areas included in the changed first multi-trip 101B is "3" (areas A, B, and C), and the number of areas included in the changed second multi-trip 102B is "1" (area B).
[0133] Therefore, according to Equation 5, the total cost value of the first and second multi-trips after the change is 3+1=4.
[0134] When the total cost value (4) before the change is compared with the total cost value (4) after the change, the total cost value before the change and the total cost value after the change are the same, so it is determined that the change will not reduce the cost.
[0135] Fig. 21 is a diagram showing first and second multi-trips before change as a third example according to embodiment 1. Fig. 22 is a diagram showing first and second multi-trips after change as a third example according to embodiment 1.
[0136] As shown in Figure 21, the first multi-trip 101A before the change has the most delivery destinations in area A, which is "4", and the second multi-trip 102A before the change has the most delivery destinations in area B or area C, which is "3".
[0137] Therefore, according to Equation 4, the total cost value of the first and second multi-trips before the change is (1 / 4+1 / 3)=7 / 12.
[0138] As shown in FIG. 22, the first multi-trip 101B after the change has the most delivery destinations in area A, which is "4," and the second multi-trip 102B after the change has the most delivery destinations in area B, which is "3."
[0139] Therefore, according to Equation 4, the total cost value of the first and second multi-trips after the change is (1 / 4+1 / 3)=7 / 12.
[0140] When comparing the total cost value before the change (7 / 12) with the total cost value after the change (7 / 12), the total cost value before the change and the total cost value after the change are the same, so it is determined that the change will not reduce the cost.
[0141] Alternatively, as shown in FIG. 21, the number of areas included in the first multi-trip 101A before the change is "2" (areas A and B), and the number of areas included in the second multi-trip 102A before the change is "2" (area B and area C).
[0142] Therefore, according to Equation 5, the total cost value of the first and second multi-trips before the change is 2+2=4.
[0143] As shown in FIG. 22, the number of areas included in the first multi-trip 101B after the change is "3" (areas A, B, and C), and the number of areas included in the second multi-trip 102B after the change is "2" (areas B and C).
[0144] Therefore, according to Equation 5, the total cost value of the first and second multi-trips after the change is 3+2=5.
[0145] When the total cost value before the change (4) is compared with the total cost value after the change (5), the total cost value after the change is greater than the total cost value before the change, so it is determined that the change has increased the cost. In this case, the delivery plan creation unit 21 sets the multi-trip before the change as the current solution.
[0146] <Modification of Implementation Means 2> In the above-described implementation means 2, the cost calculation unit 22 calculates the inter-trip neighborhood cost of a multi-trip from the cost calculated by either Equation 4 or Equation 5. However, the cost calculation unit 22 may calculate the inter-trip neighborhood cost of a multi-trip by combining the costs calculated by Equation 4 and Equation 5. For example, the cost calculation unit 22 may calculate the total cost of a multi-trip using the following Equation 6.
[0147] Inter-trip proximity cost = inverse of the maximum number of destinations in the same area included in a multi-trip * cost coefficient + number of areas included in the multi-trip * cost coefficient ... (Equation 6)
[0148] In this case, the priority evaluation of the cost calculated from Equation 4 or Equation 5 can be adjusted by the value of the cost coefficient. When the inter-trip neighborhood cost is calculated as the weighted sum of the cost of Equation 4 and the cost of Equation 5, as in Equation 6, the cost coefficients multiplied by the costs corresponding to Equation 4 and Equation 5 correspond to the weights of each cost. In this case, the cost coefficients indicate the weights of each cost, so they can each be different values.
[0149] (Summary of the first embodiment) The above description of the first embodiment discloses the following techniques.
[0150] <Technology 1> A delivery planning device (1) that creates a delivery plan according to the first embodiment includes a processor (11) and a memory (12), and the processor works in cooperation with the memory to calculate the cost of a multi-trip that includes multiple trips that start from a base, visit at least one delivery destination, and return to the base, based on the relationships between the multiple trips included in the multi-trip. This allows the cost of multiple trips to be calculated based on the relationships between the multiple trips.
[0151] <Technology 2> In the delivery planning device described in Technique 1, the processor calculates the cost based on distances between the plurality of trips included in the multi-trip. This allows for the calculation of costs for multiple trips based on the distance between the trips.
[0152] <Technology 3> In the delivery planning device described in Technology 2, the processor calculates single-trip representative coordinates, which are representative coordinates of the trip, based on the coordinates of one or more delivery destinations included in the trip, calculates total trip representative coordinates based on the multiple single-trip representative coordinates, and calculates the cost based on the distance between the total trip representative coordinates and each of the single-trip representative coordinates. This allows the cost of a multi-trip to be calculated based on the distance between the total trip representative coordinates and each single trip representative coordinate.
[0153] <Technology 4> In the delivery planning device according to any one of techniques 1 to 3, the processor calculates the cost based on directions between the plurality of trips included in the multi-trip. This allows costs for multiple trips to be calculated based on the direction between the trips.
[0154] <Technology 5> In the delivery planning device described in Technology 4, the processor calculates single-trip representative coordinates, which are representative coordinates of the trip, based on the coordinates of one or more delivery destinations included in the trip, calculates angles formed by lines connecting the base and each of the single-trip representative coordinates, and calculates the cost based on the maximum angle among the calculated angles. This allows the cost of a multi-trip to be calculated based on the maximum angle formed by the lines connecting the base point and the representative coordinates of each single trip.
[0155] <Technology 6> In the delivery planning device according to any one of techniques 1 to 5, a plurality of areas are set, and the processor calculates the cost based on which area each delivery destination included in the multi-trip belongs to. This allows the cost related to the multi-trip to be calculated based on the area to which each delivery destination included in the multi-trip belongs.
[0156] <Technology 7> In the delivery planning device described in Technique 6, the processor calculates the cost based on the reciprocal of the maximum number of delivery destinations belonging to each area. This allows the cost for a multi-trip to be calculated based on the reciprocal of the maximum number of delivery destinations belonging to each area.
[0157] <Technology 8> In the delivery planning device described in Technique 6, the processor calculates the cost based on the number of areas to which each delivery destination included in the multi-trip belongs. This allows the cost of a multi-trip to be calculated based on the number of areas to which each delivery destination included in the multi-trip belongs.
[0158] <Technology 9> In the delivery planning device according to any one of techniques 6 to 8, the processor displays delivery destinations belonging to different areas in different ways. This allows you to visually determine which area each delivery destination belongs to.
[0159] <Technology 10> In the delivery planning device according to any one of techniques 6 to 9, when the trip spans a plurality of areas, the processor displays the route of the trip in a different manner for each area. This allows you to visually determine which areas your trip route passes through.
[0160] <Technology 11> In the delivery planning device described in any one of Techniques 1 to 10, the multi-trip includes a first multi-trip and a second multi-trip, and the processor calculates a total cost value before the change by adding up the cost related to the first multi-trip and the cost related to the second multi-trip, changes the configuration of trips included in the first multi-trip and the second multi-trip to generate a modified first multi-trip and a modified second multi-trip, calculates a total cost value after the change by adding up the cost related to the modified first multi-trip and the cost related to the modified second multi-trip, and compares the total cost value before the change with the total cost value after the change. This allows the search for a lower-cost multi-trip by repeatedly changing the trip configuration.
[0161] <Technology 12> A delivery planning method for creating a delivery plan using a computer according to embodiment 1 calculates the cost of a multi-trip that includes multiple trips that start from a base, visit at least one delivery destination, and return to the base, based on the relationships between the multiple trips included in the multi-trip. This allows the cost of multiple trips to be calculated based on the relationships between the multiple trips.
[0162] <Technology 13> The delivery planning program for creating a delivery plan according to the first embodiment causes a computer to calculate the cost of a multi-trip that includes multiple trips that start from a base, visit at least one delivery destination, and return to the base, based on the relationships between the multiple trips included in the multi-trip. This allows the cost of multiple trips to be calculated based on the relationships between the multiple trips.
[0163] Although the embodiments have been described above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that a person skilled in the art can conceive of various modifications, alterations, substitutions, additions, deletions, and equivalents within the scope of the claims, and it is understood that these also fall within the technical scope of the present disclosure. Furthermore, the components in the above-described embodiments may be combined in any manner without departing from the spirit of the invention. [Industrial Applicability]
[0164] The techniques of the present disclosure are useful for creating delivery plans. [Explanation of symbols]
[0165] 1. Delivery planning device 2. User terminal 3. Communication Network 11 processors 12 Memory 13. Storage 14 Communications Department 31 Area Information DB 32 Baggage information DB 33 Vehicle Information DB 34 Distance matrix DB 21 Delivery Planning Department 22 Cost Calculation Department 23 Distance matrix generator 31 Area Information DB 32 Baggage information DB 33 Vehicle Information DB 34 Distance matrix DB 200 maps 201 Border
Claims
1. A delivery planning device for creating a delivery plan, comprising: a processor and a memory; The processor, in cooperation with the memory, Calculating a cost related to a multi-trip including multiple trips that start from a base, visit at least one delivery destination, and return to the base, based on the relationship between the multiple trips included in the multi-trip; Delivery planning device.
2. the processor calculates the cost based on distances between the plurality of trips included in the multi-trip; The delivery planning device according to claim 1 .
3. The processor: Calculating single trip representative coordinates that are representative coordinates of the trip based on coordinates of one or more delivery destinations included in the trip; calculating a total trip representative coordinate based on the plurality of single trip representative coordinates; calculating the cost based on a distance between the total trip representative coordinate and each of the single trip representative coordinates; The delivery planning device according to claim 2 .
4. the processor calculates the cost based on directions between the plurality of trips included in the multi-trip; The delivery planning device according to claim 1 .
5. The processor: Calculating single trip representative coordinates that are representative coordinates of the trip based on coordinates of one or more delivery destinations included in the trip; Calculating the angle formed by the straight lines connecting the base and each of the single trip representative coordinates; calculating the cost based on the maximum angle among the calculated angles; The delivery planning device according to claim 4.
6. Several areas are set up, The processor calculates the cost based on which area each delivery destination included in the multi-trip belongs to. The delivery planning device according to claim 1 .
7. the processor calculates the cost based on the reciprocal of the maximum number of delivery destinations belonging to each area; The delivery planning device according to claim 6.
8. The processor calculates the cost based on the number of areas to which each delivery destination included in the multi-trip belongs. The delivery planning device according to claim 6.
9. The processor displays delivery destinations belonging to different areas in different manners. The delivery planning device according to claim 6.
10. When the trip spans multiple areas, the processor displays the route of the trip in a different manner for each area. The delivery planning device according to claim 6.
11. the multi-trips include a first multi-trip and a second multi-trip; The processor: calculating a total cost value before the change by adding together the cost related to the first multi-trip and the cost related to the second multi-trip; modifying the configuration of trips included in the first multi-trip and the second multi-trip to generate a modified first multi-trip and a modified second multi-trip; calculating a total cost value after the change by adding together the cost related to the first multi-trip after the change and the cost related to the second multi-trip after the change; comparing the total cost value before the change with the total cost value after the change; The delivery planning device according to any one of claims 1 to 10.
12. A delivery planning method for creating a delivery plan using a computer, comprising: Calculating a cost related to a multi-trip including multiple trips that start from a base, visit at least one delivery destination, and return to the base, based on the relationship between the multiple trips included in the multi-trip; Delivery planning methods.
13. A delivery plan program for creating a delivery plan, Calculating a cost related to a multi-trip including multiple trips that start from a base, visit at least one delivery destination, and return to the base, based on the relationship between the multiple trips included in the multi-trip; A delivery planning program that allows a computer to do this.
Citation Information
Patent Citations
Road learning model generation device, road learning model generation method, delivery planning generation device and delivery planning generation method
JP2019082755A