Delivery planning apparatus, method, and program

Abstract

To provide a delivery planning apparatus which can make a delivery plan.SOLUTION: The present invention is directed to a delivery planning apparatus for creating a delivery plan including division delivery in which a plurality of cargoes is delivered by a plurality of vehicles to a plurality of delivery destinations from the delivery base. The apparatus has a candidate delivery plan generating unit for allocating one or a plurality of cargoes to each of the vehicles as allocated cargoes, for determining each of delivery routes of the plurality of vehicles upon delivery of the allocated cargoes allocated by each vehicle by each of the vehicle to each of the delivery destinations, and for thus generating a plurality of candidate delivery plans, a cost acquiring unit for, with respect to each of the candidate delivery plans, acquiring travel costs resulting from travel of each delivery route by each vehicle and stay costs resulting from stay of each of the vehicles at each of the plurality of delivery destinations, and a selection unit for selecting one or a plurality of delivery plans from the plurality of candidate delivery plans based on the total costs calculated from the travel costs and the stay costs of the plurality of candidate delivery plans.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a delivery planning device, method, and program capable of creating a delivery plan for goods departing from a logistics base (hereinafter also referred to as a depot) in a logistics system and being delivered to multiple destinations. [Background technology]

[0002] Patent Document 1 describes a delivery planning device that solves the problem of delivery planning and enables delivery planning for cargo to be delivered to multiple destinations. The device includes an input device for inputting information on each order and master data related to delivery planning, a processing device for creating a delivery plan in which multiple vehicles deliver cargo to multiple destinations, an output device for outputting the created delivery plan, and an order grouping means for dividing orders and creating groups based on distance data between destinations, and causing the device to execute a delivery planning process for each divided order group. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2004-238129 [Overview of the Initiative] [Problems that the invention aims to solve]

[0004] The delivery planning problem is the problem of finding the shortest total distance traveled when multiple vehicles depart from a depot and deliver goods to multiple destinations. The general method for solving the delivery planning problem is to formulate the problem conditions into a mathematical formula (objective function) and solve it using a computer. Generally, the change in the value of the objective function (total distance traveled) with respect to computation time converges exponentially to a certain distance. Patent document 1 describes a delivery planning method that speeds up computation by geographically grouping delivery destinations that are close in distance and limiting the delivery route to within that group, thereby reducing the search space.

[0005] However, in conventional delivery planning methods, including the method described in Patent Document 1, if the demand for a single delivery destination exceeds the loading capacity of a transport vehicle, it is necessary to consider dividing the large amount of cargo to be delivered or dispatching multiple vehicles. Such a delivery method, which divides cargo for a single delivery destination into multiple vehicles, known as the split delivery method, becomes complex for many delivery destinations and large amounts of cargo. Therefore, planning a delivery using the split delivery method is difficult and inevitably relies on the intuition and subjective skills of experienced delivery planners.

[0006] The present invention has been made in view of the problems of the prior art described above, and one example of its objective is to provide a delivery planning device, method, and program that can automate the creation of delivery plans using a segmented delivery method. [Means for solving the problem]

[0007] The present invention is a delivery planning device that creates a delivery plan including split deliveries when delivering multiple packages destined for multiple destinations from one delivery base to multiple destinations using multiple vehicles, A candidate delivery plan generation unit that assigns one or more of the multiple packages to each of the multiple vehicles as assigned packages, and determines the respective delivery routes for each of the multiple vehicles when each of the multiple vehicles delivers the assigned packages to their respective delivery destinations, thereby generating multiple candidate delivery plans. For each of the candidate delivery plans, a cost acquisition unit acquires travel costs, which are the costs incurred when each of the multiple vehicles travels along each of the delivery routes, and stay costs, which are the costs incurred when each of the multiple vehicles stays at each of the multiple delivery destinations. A selection unit that selects one or more delivery plans from the plurality of candidate delivery plans based on the total cost calculated based on the travel cost and the stay cost, It is characterized by including.

[0008] The present invention relates to a delivery planning method, which is performed by a delivery planning device that creates a delivery plan including split deliveries when delivering multiple packages destined for multiple destinations from one delivery base to multiple destinations using multiple vehicles. A candidate delivery plan generation step involves assigning one or more of the multiple packages to each of the multiple vehicles as assigned packages, and determining the respective delivery routes for each of the multiple vehicles when each of the multiple vehicles delivers the assigned packages to their respective delivery destinations, thereby generating multiple candidate delivery plans. A cost acquisition step for each of the candidate delivery plans, which involves acquiring travel costs, which are the costs incurred when each of the multiple vehicles travels along each of the delivery routes, and stay costs, which are the costs incurred when each of the multiple vehicles stays at each of the multiple delivery destinations. A selection step of selecting one or more delivery plans from the plurality of candidate delivery plans based on the total cost calculated based on the travel cost and the accommodation cost, It is characterized by including.

[0009] The present invention provides a delivery planning program for a computer in a delivery planning device that creates a delivery plan including split deliveries when multiple packages destined for multiple destinations are delivered from one delivery base to multiple destinations using multiple vehicles. A candidate delivery plan generation step involves assigning one or more of the multiple packages to each of the multiple vehicles as assigned packages, and determining the respective delivery routes for each of the multiple vehicles when each of the multiple vehicles delivers the assigned packages to their respective delivery destinations, thereby generating multiple candidate delivery plans. A cost acquisition step for each of the candidate delivery plans, which involves acquiring travel costs, which are the costs incurred when each of the multiple vehicles travels along each of the delivery routes, and stay costs, which are the costs incurred when each of the multiple vehicles stays at each of the multiple delivery destinations. A selection step of selecting one or more delivery plans from the plurality of candidate delivery plans based on the total cost calculated based on the moving cost and the staying cost from the plurality of candidate delivery plans, characterized by causing the execution thereof.

Effect of the Invention

[0010] According to the delivery plan creation apparatus, method, and program of the present invention, for example, in the split delivery method, it is possible to prevent excessive splitting (splitting of delivery destinations and splitting of delivery quantities) and improve the loading rate of vehicles.

[0011] When calculating a delivery plan considering split delivery, even if it is a split that can reduce the delivery cost, there are cases where a plan considering the psychological burden on the driver side is required. To address such issues, a virtual cost for stopping at a delivery destination is defined, and the threshold value of the virtual cost is calculated by back-calculating from the plan calculated by the system and the plan modified by a user such as a delivery plan person in charge, and reflected in the creation of subsequent plans, thereby improving the delivery plan.

Brief Description of the Drawings

[0012] [Figure 1] It is a configuration diagram for explaining an example of normal delivery. [Figure 2] It is a configuration diagram for explaining an example of split delivery. [Figure 3] It is a schematic configuration diagram showing an example of the configuration example of the delivery plan creation system 100 of the embodiment. [Figure 4] It is a schematic configuration diagram showing an example of the configuration example of the delivery plan creation apparatus 10 of the embodiment. [Figure 5] It is a flowchart showing an example of a delivery plan creation method of the operation of the delivery plan creation apparatus of the embodiment.

Modes for Carrying Out the Invention

[0013] Hereinafter, a delivery plan creation system 100 including a delivery plan creation device 10 according to an embodiment of the present invention will be described while referring to the drawings.

[0014] [Overview] Delivery plan creation is a delivery route problem of "finding the route with the minimum cost for delivering a predetermined amount of goods from a depot (delivery base n0) to a plurality of delivery destinations" (where the route is the route from the depot until the delivery vehicle returns to the depot). The basic conditions of the standard delivery route problem (ordinary delivery) are as follows. 1. One vehicle travels one route and the loading capacity does not exceed the capacity of the vehicle. 2. The number of vehicles (number of routes) does not exceed the upper limit. 3. At one delivery destination, the demand is delivered only once by one vehicle. 4. The total delivery cost is a function of the delivery distance (delivery time), the number of vehicles, etc.

[0015] Note that the "delivery cost" is the cost required for delivering goods. The way of expressing the cost is not particularly limited. For example, the delivery cost may include the delivery distance (delivery time), the amount of money required for delivering the goods itself, or a value obtained by converting the amount of money required for delivering the goods by a predetermined algorithm. Alternatively, the delivery cost may include costs other than the money required for delivering the goods (for example, the number of personnel boarding the vehicle for delivery work, etc.).

[0016] <0​​​​Here's a brief explanation of examples of standard and split deliveries.

[0018] As shown in Figure 1, in a typical delivery, the goods are delivered from the depot (delivery hub n0) by vehicle A to destination n1 with a demand of 2 pallets, by vehicle B to destination n2 with a demand of 4 pallets, and by vehicle C to destination n3 with a demand of 2 pallets, each making a round trip.

[0019] In this standard delivery system, one vehicle makes only one delivery to each destination to meet the demand, requiring three vehicles and a total travel distance of 160 km (travel cost).

[0020] As shown in Figure 2, in split delivery, the goods are delivered from the depot (delivery base n0) by each vehicle: Vehicle A delivers 2 pallets to destination n1, Vehicle A delivers 2 pallets from destination n1 to destination n2, Vehicle B delivers 2 pallets to destination n3, and Vehicle B delivers 2 pallets from destination n3 to destination n2.

[0021] In this split delivery, two vehicles with increased loading capacity (vehicle A: 4 pallets loaded, vehicle B: 4 pallets loaded) are used to deliver the required amount (2+2 pallets) to destination n2 in two separate trips using these two vehicles. In addition, with this split delivery, the total distance traveled by all two vehicles is 120 km (travel cost).

[0022] In standard delivery (Figure 1), one vehicle is allocated to each delivery destination, requiring the use of three vehicles. In contrast, split delivery (Figure 2) allows the allocated demand to be delivered using only two vehicles. Furthermore, the total distance traveled is 40 km lower with split delivery. Split delivery allows for cost reductions in distance and vehicle usage, especially when dealing with large amounts of cargo, by dividing specific demands into separate deliveries.

[0023] In recent years, the logistics industry has faced a labor shortage, resulting in a lack of resources such as delivery vehicles and drivers. Therefore, to deliver a large volume of goods using fewer resources, split delivery allows for efficient delivery routes, as exemplified by the two vehicles mentioned above, improving the loading efficiency of each vehicle.

[0024] Thus, split delivery, where packages are divided among multiple vehicles for a single delivery destination, has the advantage of increasing vehicle loading efficiency and enabling more efficient delivery. The larger the package, the more the distance and number of vehicles can be reduced by splitting the delivery. However, a disadvantage of split delivery is that the delivery method becomes more complex, making it difficult to plan a delivery schedule that includes split delivery.

[0025] Furthermore, the theoretical optimal solution derived by the optimization algorithm for split delivery results in excessive splitting for a single delivery destination. Excessive splitting (splitting of delivery destinations and splitting of delivery volume) presents the following problems: • The workload at the delivery destination increases, and the burden on the recipient at the delivery destination increases. • Fixed costs will increase due to the increase in the number of vehicles. • The effort required for delivery management will increase. • Operations become more complex and increase in number.

[0026] Therefore, in this embodiment, as a solution to the problem of split delivery, we assume that a virtual cost is incurred each time a vehicle stops at a delivery destination, and calculate an optimal solution in the objective function that suppresses excessive splitting.

[0027] When multiple vehicles depart from a depot to deliver goods to multiple destinations, the problem of minimizing the total distance traveled (travel cost) in a delivery planning scenario can be represented mathematically using the following constants and variables as shown in equations (1) to (9).

[0028] The objective function in equation (1) represents minimizing the total vehicle travel cost and the virtual cost of all deliveries. Equations (2) through (9) represent the constraints.

[0029] (constant) m: Number of vehicles, n: Number of delivery destinations, i,j: Subscripts representing the delivery destination (0 is the depot, others are the delivery destination). k: Subscript indicating a vehicle, di: Demand for delivery destination i (multiple packages addressed to multiple delivery destinations), c ij : Distance from delivery destination i to delivery destination j, q k : Maximum load capacity (capacity) of vehicle k, vik: Virtual cost due to vehicle k's stay at delivery destination i, (variable) x ijk : A 0-1 variable (binary variable) that indicates whether vehicle k directly visited or did not visit delivery destination i to j. y ik : A 0-1 variable (binary variable) that indicates whether or not delivery was made to destination i by vehicle k. z ik : A real number variable indicating the amount of delivery by vehicle k to destination i.

[0030]

number

[0031] (constraint conditions) Equation (2) shows that the number of vehicles is in the m range. Equation (3) implies the constraint that each delivery destination i must be divided and delivered by one or more vehicles. Here, the number of vehicles m is constant regardless of the vehicle's capacity, i.e., q k When =q (k=1,...,m), the minimum number of vehicles is given by Σdi / q, and delivery is possible with that number of vehicles. Equation (4) shows that the amount delivered by vehicle k to destination i is 0 if yik is 0, and if delivery takes place, zik is less than or equal to di. Equation (5) shows that the total volume of deliveries by all vehicles to delivery destination i matches the demand. Equation (6) shows that the total amount delivered by vehicle k is equal to the vehicle capacity q. k This indicates that it will not exceed [a certain value]. Equation (7) means that if destination j is being delivered by vehicle k, then vehicle k will come from some destination with respect to destination j. Similarly, in equation (8), if destination i is being delivered by vehicle k, it means that vehicle k is going from destination i to some other destination. Equation (9) is a constraint that excludes subtours.

[0032] In this delivery planning problem, the first term of the objective function equation (1) represents the total travel cost of the vehicle, and the second term represents the total virtual cost associated with stays at multiple delivery destinations. The virtual cost vik in the second term of equation (1) represents a penalty for splitting the delivery quantity to suppress excessive splitting; therefore, a larger virtual cost allows for a solution with fewer package splits.

[0033] The constant virtual cost vik is a stay cost corresponding to the time spent at the delivery destination i, including the time spent unloading goods and other tasks during the vehicle k's visit, and is calculated from that work time. For example, when making a stop at a delivery destination, the virtual cost vik will include, for example, the stay costs, i.e., time costs, as shown in (1) and (2) below. (1) Basic cost B (fixed cost for each delivery visit): Time spent on tasks such as entering and exiting the parking lot, unlocking and locking doors, and inputting data into communication terminals. (2) Usage-based cost U (cost based on the amount of goods delivered at the time of delivery visit): time spent on carrying goods / per cart, etc.

[0034] Therefore, the virtual cost vik can be expressed by the formula vik = base cost B + usage cost U. If these work times are known, the virtual cost (time cost) can be converted into travel costs and expense costs.

[0035] For example, a virtual cost of vik (30 minutes of work time) can be converted to the travel cost (distance of 30 km) that would have been incurred by traveling by vehicle at a speed of 60 km / h. Furthermore, since the travel cost is considered to be a variable cost U equivalent to the distance, it can be converted to an expense cost by dividing it by the fuel cost (yen / distance).

[0036] In addition, the distance cij (moving cost) from delivery point i to delivery point j, which is a constant in the first term of the objective function formula (1) for the total moving cost of the vehicle, can be converted into cost cost or time cost in the same way as the virtual cost.

[0037] Note that the stay cost further varies depending on the scale of facilities such as berths, parking lots, and handling equipment at each delivery point where the vehicle stays. Therefore, these are quantified and calculated based on the numerical values of the scale.

[0038] (Input data · Output data) As input data, the number of vehicles m, the number of delivery points n, the demand di (weight, number of pallets, number of cases, etc.) at delivery point i, the distance cij from delivery point i to delivery point j (distance between the moving origin and the moving destination (moving time · speed)), and the maximum loading capacity (capacity) q of vehicle k k And there is a virtual cost vik caused by the stay of vehicle k at delivery point i, which is a constant. Substituting these into the objective function formula (1), as output data, a value close to the minimum value of the total moving distance (total moving cost) as the solution of the formula, the delivery order and vehicle allocation group (shared delivery volume of goods) of multiple vehicles in split route delivery are automatically derived from a huge number of combinations. As a result, a delivery plan can be obtained that can reduce fuel costs and CO2 emissions.

[0039] Note that when converting the total moving distance to the minimum value of the total cost as the solution of the objective function formula (1), the constant distance c ij (distance from delivery point i to delivery point j) can be converted into running fuel cost (cost cost) and toll road tolls such as highway tolls can be included in the cost cost.

[0040] Note that as the number of delivery points and the number of vehicles for transportation increase, the number of variables also increases accordingly. The number of combinations of possible variables and constants also increases exponentially, making it difficult to solve the objective function. Therefore, in order to shorten the calculation time, it is preferable to determine the priority order to exclude combinations of options with low possibility from all combinations and calculate the optimal solution.

[0041] Furthermore, since delivery rules vary widely depending on the shipper's requirements and the logistics operator's experience, in order to achieve efficiency, the above mathematical model of a typical delivery plan, including split deliveries, needs to be modified (constrained) to take into account the shipper's requirements and the logistics operator's delivery rules.

[0042] As an example of delivery rules, for example, for the mathematical model above, let's assume the number of delivery destinations is approximately 50 stores, and the delivery requirement is a rule using a constant number of vehicles m = a × (m1 + m2) consisting of m1 large vehicles (maximum cargo capacity q1) and m2 small vehicles (maximum cargo capacity q2). Then, each vehicle is assumed to operate an average of a trips per day. If it is possible to deliver to w stores per trip (equation (10)), and some delivery destinations P can be divided into deliveries up to a maximum of g vehicles (equation (11)), and the remaining delivery destinations Q cannot be divided into deliveries (equation (12)), then the following constraints (10) to (11) can be modified or added to the mathematical model above.

[0043]

number

[0044] Based on the above example of delivery rules, the usefulness of a cost-minimizing dispatch algorithm (objective function of the total vehicle movement cost and virtual cost in equation (1)) that takes delivery conditions (bulk / split) into consideration was verified in the planning of actual route delivery operations.

[0045] We implemented an automated calculation of delivery plans, limiting it to 30 minutes of planning time available to the delivery planner on-site. By comparing the actual route delivery data (number of vehicle trips (number of routes), total distance traveled) with the values ​​calculated by the same algorithm, we confirmed that the number of split delivery destinations could be reduced, and efficiency could be improved in both total delivery distance (travel cost) and vehicle loading rate, without relying on the experience of the person in charge. [Examples]

[0046] Figure 3 is a schematic diagram showing an example of the configuration of the delivery planning system 100 of this embodiment based on the embodiment.

[0047] [Delivery Planning System] The delivery planning system 100 consists of a delivery planning device 10 that can communicate with each other via the Internet through a network NW, and a communication terminal 101 attached to each vehicle A, B, C, or the driver of the vehicle (or worker performing tasks such as unloading).

[0048] The delivery planning device 10 is a computer device that functions as a server. The delivery planning device 10 is connected to multiple communication terminals 101 so that they can communicate with each other.

[0049] The communication terminal 101 is a user interface device that generally includes a touch panel or display and an operating unit, and is a computer device that has the function of measuring location information, acceleration information, etc., and transmitting this information to the delivery planning device 10.

[0050] Examples of communication terminals 101 include smartphones capable of internet communication, personal computers (PCs) (not shown), and tablet PCs with functions equivalent to those of a smartphone. Furthermore, examples of communication terminals 101 include mobile communication devices (not shown) such as navigation systems or drive recorders mounted on vehicles such as trucks. Note that the navigation system or drive recorder may be a communication-enabled tablet PC, notebook PC, or smartphone that runs a predetermined navigation or drive recorder application. Thus, communication terminal 101 can measure the actual position, speed, etc. of vehicles A, B, and C and transmit this information to the delivery planning device 10 via the internet.

[0051] The communication terminal 101 has a corresponding application program installed for linking with the delivery planning device 10 and other communication terminals. This allows for communication settings such as URL (Uniform Resource Locator) and access point AC settings, and encryption key settings. In other words, the vehicle driver (or worker performing tasks such as unloading) can transmit measured location information, acceleration information, and other data to the delivery planning device 10 by operating the touch panel or display and control unit of the communication terminal 101, or automatically.

[0052] [Delivery planning device] As shown in Figure 4, the delivery planning device 10 is a computer device and includes a CPU (Central Processing Unit) 11, a storage device 12, an input unit 13 and an output unit 14 which are interfaces for inputting parameters from users such as delivery planners and returning calculation results to the users, and a communication unit 15, all connected to each other by an internal bus (not shown). Input parameters are input to the delivery planning device 10 via the input unit 13 and the communication unit 15. The input parameters are the number of vehicles m, the number of delivery destinations n, the demand amount di at delivery destination i, the distance cij from delivery destination i to delivery destination j, and the maximum load capacity (capacity) q of vehicle k. k , and the virtual cost vik due to the vehicle k's stay at delivery destination i.

[0053] The storage device 12 includes, for example, RAM (Random Access Memory), HDD (Hard Disk Drive), SD (Solid State Drive), and flash memory, which store various programs and data and also serve as the CPU 11's work area. The input unit 13 includes, for example, a keyboard, mouse, touch panel, and numeric keypad for inputting data. The output unit 14 includes, for example, a display for user display and a touch panel for outputting data. The communication unit 15 communicates with the Internet via a network NW, either wired or wirelessly, to send and receive data. The input unit 13 and output unit 14 also include USB (Universal Serial Bus) for connecting external devices, such as recording media.

[0054] The CPU 11 controls the overall operation of the delivery planning device, following the operating system (OS) software program installed in the storage device 12 and the application program for delivery planning (hereinafter referred to as the delivery planning program).

[0055] Examples of delivery planning devices 10 include server devices and personal computers (PCs) that are capable of communicating with other network devices such as PCs via wired or wireless internet connections.

[0056] The delivery planning program installed in the delivery planning device 10 is loaded into the storage device 12, and the CPU 11 executes the application software held in the storage device 12, thereby functioning as the following (1) to (4) functional units. Through these functional units, the delivery planning device 10 creates a delivery plan that includes split deliveries when delivering multiple packages (zik(i=1~n,k=1~m): delivery volume by vehicle k to delivery destination i) from a delivery base n0 to multiple delivery destination i using multiple vehicles.

[0057] (1) Candidate Delivery Plan Generation Unit FCT: This generates multiple candidate delivery plans for route travel that minimize the above objective function, which is a formula for the total distance traveled by a vehicle from a delivery base, through the route between delivery destinations, and back to the delivery base, based on the constraints. above The above objective function minimizes the travel costs and accommodation costs described above. Solution This is calculated based on the constraints.

[0058] (2) Input parameter storage unit PKP: This stores input parameters such as constants, variables, and constraints of the delivery plan.

[0059] (3) Cost acquisition unit FJP: This is also used to calculate the objective function and acquires the travel cost incurred when each vehicle k travels along each part of the delivery route and the stay cost when each vehicle k delivers goods to each delivery destination i (virtual cost vik(i=1~n,k=1~m)) based on the time vehicle k stays at delivery destination i.

[0060] (4) Selection Unit DCT: This unit selects one or more delivery plans from multiple candidate delivery plans based on the total cost calculated based on travel costs and accommodation costs vik, and sends the result to the output unit 14. The output unit 14 temporarily holds the result.

[0061] (Operation description) The operation (delivery planning method) when a user, such as a delivery planner, uses the delivery planning device 10 to calculate a delivery route will be explained using Figure 5.

[0062] The user provides the delivery planning device 10 with input parameters (constants of the objective function such as distance traveled between delivery destinations, number of vehicles, and cargo volume, as well as constraints such as variables and virtual costs) and a calculation limit (upper limit of calculation time) via the input unit 13 of the delivery planning device 10 (step S1). The delivery planning device 10 then acquires the input parameters, which are stored in the input parameter storage unit PKP by the CPU (input parameter acquisition step). At this point, the CPU starts a timer to measure the calculation limit.

[0063] The candidate delivery plan generation unit FCT minimizes the total distance traveled by a vehicle from a delivery base, along a delivery route, and back to the delivery base, based on the input parameters of the input parameter storage unit PKP and the above-formulated objective function, and generates multiple candidate delivery plans including the delivery order and vehicle assignments for multiple vehicles in a split delivery (Step S2: Candidate Delivery Plan Generation Step). Subsequently, the cost acquisition unit FJP acquires the above-mentioned travel costs and the stay costs (virtual cost vik) when each vehicle k delivers goods to each delivery destination i (Step S3 (Cost Acquisition Step)). Subsequently, in Step S3, the selection unit DCT selects one or more delivery plans from the multiple candidate delivery plans based on the total cost calculated based on the travel costs and stay costs vik (Selection Step), and sends the result to the output unit 14.

[0064] In steps S2 and S3, the delivery planning device 10 assigns cargo zik to each vehicle k as assigned cargo, determines the respective delivery routes for each vehicle k when delivering the assigned cargo to each destination of said cargo, and generates one or more delivery plans.

[0065] Next, the CPU transmits input parameters such as the measured position and speed of the delivery vehicle, which were measured by the communication terminal 101, to the delivery planning device 10 via the internet and determines whether they are stored in the input parameter storage unit PKP (step S4).

[0066] If the measured values ​​are stored in the input parameter storage unit PKP (step S4:Y), the CPU calculates a new stay cost based on the measured values ​​in the algorithm of steps S2 and S3 (actual actual stay cost) based on the actual transmission results (measured values) (step S5). The CPU compares this actual stay cost with the virtual cost in the algorithm of steps S2 and S3 (step S6). If the actual stay cost is lower than the virtual cost (step S7:Y), the CPU updates the virtual cost stored in the input parameter storage unit PKP with the actual stay cost (feedback) in the update process (step S8) and sends the result to the output unit 14. The output unit 14 temporarily holds the result. In other words, the CPU sets the actual stay cost as the ideal threshold (learns) and improves the accuracy of the retained virtual cost.

[0067] If the measured value is not stored in the input parameter storage unit PKP (step S4:N), or if an update process (step S8) is performed, the result is returned to the user via the output unit 14 (step S9).

[0068] In the result output step (step S9), the CPU checks for termination conditions. These termination conditions include the computation time limit obtained in step S1 and the processing limit from steps S2 to S8. If the termination conditions are met, the temporary results are output and the process terminates.

[0069] In addition, input parameters include time constraints such as the designated delivery time, travel time, and loading / unloading time for each delivery, and these constraints can be added to the mathematical model described above. [Explanation of Symbols]

[0070] 10 Delivery planning device FCT Candidate Delivery Plan Generation Unit PKP Input Parameter Storage Unit FJP Cost Acquisition Department DCT Selection Section

Claims

1. A delivery planning device that creates a delivery plan including split deliveries when delivering multiple packages destined for multiple destinations from one delivery base to the multiple destinations using multiple vehicles, A candidate delivery plan generation unit that assigns one or more of the multiple packages to each of the multiple vehicles as assigned packages, and determines the respective delivery routes for each of the multiple vehicles when each of the multiple vehicles delivers the assigned packages to their respective delivery destinations, thereby generating multiple candidate delivery plans, For each of the candidate delivery plans, a cost acquisition unit acquires travel costs, which are the costs incurred when each of the multiple vehicles travels along each of the delivery routes, and stay costs, which are the costs incurred when each of the multiple vehicles stays at each of the multiple delivery destinations. A selection unit that selects one or more delivery plans from the plurality of candidate delivery plans based on the total cost calculated based on the travel cost and the stay cost, A delivery planning device that includes this.

2. The candidate delivery plan generation unit calculates a solution to the objective function that minimizes the travel cost and the stay cost based on the constraints, The cost acquisition unit acquires the actual actual stay costs from the multiple vehicles that traveled according to the candidate delivery plan selected by the selection unit. The delivery planning device according to claim 1, characterized in that the selection unit compares the actual actual stay cost with the stay cost, and updates the stay cost with the actual stay cost, using the stay cost as the ideal threshold, if the actual actual stay cost is lower than the stay cost.

3. The delivery planning device according to claim 1, characterized in that the aforementioned travel cost is calculated based on the fuel cost of each of the vehicles.

4. The delivery planning device according to claim 1, characterized in that the aforementioned stay cost is calculated based on the stay time at each of the delivery destinations where each of the vehicles stays.

5. The delivery planning device according to claim 1, characterized in that the aforementioned stay cost is calculated based on the quantified scale of facilities at each of the delivery destinations where each of the vehicles stays.

6. The delivery planning device according to claim 2, characterized in that the constraints include an upper limit on the load capacity of each of the multiple vehicles that can deliver to the multiple delivery destinations in a divided manner.

7. A delivery planning device that creates a delivery plan including split deliveries when delivering multiple packages destined for multiple destinations from one delivery base to multiple destinations using multiple vehicles, the method being used to create a delivery plan, A candidate delivery plan generation step involves assigning one or more of the multiple packages to each of the multiple vehicles as assigned packages, and determining the respective delivery routes for each of the multiple vehicles when delivering the assigned packages to their respective destinations, thereby generating multiple candidate delivery plans. A cost acquisition step for each of the candidate delivery plans, which involves acquiring travel costs, which are the costs incurred when each of the multiple vehicles travels along each of the delivery routes, and stay costs, which are the costs incurred when each of the multiple vehicles stays at each of the multiple delivery destinations. A selection step of selecting one or more delivery plans from the plurality of candidate delivery plans based on the total cost calculated based on the travel cost and the accommodation cost, Delivery planning methods including

8. A computer in a delivery planning device creates a delivery plan that includes split deliveries when multiple packages destined for multiple destinations are delivered from one delivery base to multiple destinations using multiple vehicles. A candidate delivery plan generation step involves assigning one or more of the multiple packages to each of the multiple vehicles as assigned packages, and determining the respective delivery routes for each of the multiple vehicles when delivering the assigned packages to their respective destinations, thereby generating multiple candidate delivery plans. A cost acquisition step for each of the candidate delivery plans, which involves acquiring travel costs, which are the costs incurred when each of the multiple vehicles travels along each of the delivery routes, and stay costs, which are the costs incurred when each of the multiple vehicles stays at each of the multiple delivery destinations. A selection step of selecting one or more delivery plans from the plurality of candidate delivery plans based on the total cost calculated based on the travel cost and the accommodation cost, A program characterized by causing the execution of a specific action.

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