Delivery plan creation method and device

Abstract

To provide a delivery planning method which can reduce a calculation amount while properly keeping the flexibility of route selection in delivery planning.SOLUTION: A delivery planning method for creating a patrol route in which an objective function obtained by formulating the sum of the total travel distance of a vehicle from the departure from the delivery base to the return to the delivery base after traveling by a distance of a route between the delivery destinations is minimum calculates the objective function by previously excluding routes up to the exclusion ratio exceeding 0% in the descending order of the distance from the longest route in the N-1 routes from one delivery destination toward other N-1 delivery destinations before obtaining the objective function when delivering cargoes from one delivery base to the N delivery destinations.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a delivery plan creation method and device that can create a delivery plan for departing from a logistics base (hereinafter also referred to as a depot) in a logistics system and delivering packages to multiple delivery destinations. [Background technology]

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

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2004-238129 Summary of the Invention [Problem to be solved by the invention]

[0004] The delivery planning problem is a problem of determining the shortest total travel distance when multiple delivery vehicles depart from a depot and deliver packages to multiple destinations. A common approach to delivery planning problems is to formulate the problem conditions into a mathematical equation (objective function) and solve it using a computer. Patent Document 1 describes a delivery planning method that reduces the search space and speeds up calculations by geographically grouping delivery destinations into groups that are close to each other and limiting delivery routes to within those groups.

[0005] However, in the method of Patent Document 1, because delivery destinations are grouped, there are delivery routes that cross groups, and these delivery routes are excluded. In this method, if the excluded delivery routes include a good route that minimizes the objective function, there is a possibility that a solution deviating from the optimal value will be obtained.

[0006] The present invention has been made in consideration of the above-mentioned problems of the conventional technology, and an example of an object of the present invention is to provide a delivery plan creation method and device that can reduce the amount of calculation while maintaining a moderate degree of flexibility in route selection when creating a delivery plan. [Means for solving the problem]

[0007] The delivery plan creation method of the present invention is a method for creating a circular route that minimizes an objective function that formulates the sum of the total travel distances from when a vehicle departs from a delivery base, travels the distance of the route between delivery destinations, and returns to the delivery base.When delivering goods from one delivery base to N delivery destinations, before finding the objective function, the method calculates the objective function by first excluding, from N-1 routes heading from one delivery destination to the other N-1 delivery destinations, routes with an exclusion rate exceeding 0%, in descending order of distance, from the longest route.

[0008] The delivery plan creation device of the present invention is a delivery plan creation device that creates a circular route that minimizes an objective function that formulates the sum of the total travel distances from when a vehicle departs from a delivery base, travels the distance of the route between delivery destinations, and returns to the delivery base.When delivering goods from one delivery base to N delivery destinations, the device is characterized by having a route calculation unit that calculates the objective function by excluding in advance, from N-1 routes from one delivery destination to the other N-1 delivery destinations, routes with an exclusion rate exceeding 0%, in descending order of distance, from the longest route. [Effects of the Invention]

[0009] According to the delivery schedule creation method and device of the present invention, for example, the amount of calculation of the objective function can be reduced. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a block diagram showing an example of the configuration of a delivery planning device according to an embodiment; [Figure 2] 10 is a graph illustrating the pre-exclusion of routes up to an exclusion rate M in descending order of distance from the longest route among multiple routes between delivery destinations used when calculating an objective function in the delivery plan planning method of the delivery plan planning device of the embodiment. [Figure 3] 10 is a graph showing the change in the value of the objective function (total travel distance) with respect to the calculation time executed by the delivery plan creation method of the present embodiment. [Figure 4] 10 is a flowchart showing an operation when a delivery route is calculated using the delivery plan planning device of the present embodiment. [Figure 5] 10 is a flowchart showing an operation when updating a table in an optimal M value storage unit of the delivery plan planning device of the present embodiment. [Figure 6] 10 is a graph illustrating an operation for determining an optimal M value in a table of an optimal M value storage unit of the delivery plan planning device of the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, a delivery plan creation method and a delivery plan creation device according to an embodiment of the present invention will be described with reference to the drawings. In the embodiments, components having substantially the same functions and configurations are designated by the same reference numerals, and redundant description will be omitted. [Example]

[0012] FIG. 1 is a block diagram showing a schematic configuration of a delivery plan planning device 10 that executes a delivery plan planning method according to this embodiment.

[0013] The delivery plan 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 a user and returning calculation results to the user, and a communication unit 15, all of which are connected to each other via an internal bus (not shown). Input parameters and the like are acquired by the delivery plan planning device 10 via the input unit 13 and the communication unit 15.

[0014] The storage device 12 may be, for example, a random access memory (RAM), a hard disk drive (HDD), a solid state drive (SSD), or a flash memory, which stores various programs and data and serves as a work area for the CPU 11. The input unit 13 may be, for example, a keyboard, a mouse, a touch panel, or a numeric keypad for inputting data. The output unit 14 may be, for example, a display or a touch panel for displaying data to the user for outputting data. The communication unit 15 communicates with the network device 100 (or the net) via a predetermined cable, either wired or wirelessly, to send and receive data. The input unit 13 and the output unit 14 may also include a universal serial bus (USB) for connecting an external device, for example, a recording medium.

[0015] The overall operation of the delivery plan planning device is controlled by a CPU that operates in accordance with an operating system (OS) software program installed in the storage device 12 and an application for delivery plan planning (hereinafter referred to as a delivery plan planning application).

[0016] The delivery plan planning device 10 may be a server device or a PC (Personal Computer) that is an electronic device capable of communicating with network devices 100 such as other PCs via wired or wireless communication over the Internet.

[0017] The delivery planning application is installed and stored in the storage device 12. (1) A route calculation unit FCT generates a delivery plan that creates a travel route that minimizes an objective function that formulates the total total distance traveled by a vehicle from a delivery point, traveling the route distance between delivery destinations, and returning to the delivery point, using an exclusion rate (described later); and (2) an input parameter storage unit PKP (described later in a second embodiment) for storing input parameters such as variables and constraints of the delivery plan; (3) An optimal M value storage unit FJP (described later in a second embodiment) for storing the exclusion ratio used in calculating the objective function is configured.

[0018] (First Example) The delivery plan creation method of this embodiment is executed mainly using the route calculation unit FCT in the delivery plan creation device 10.

[0019] When multiple trucks k each depart from a depot and deliver packages to multiple destinations (from destination i to destination j), the delivery planning problem of minimizing the total travel distance is solved by inputting the travel distance between destinations (distance d ij is the main input parameter), the number of vehicles, the amount of cargo to be delivered to each destination, and the maximum load capacity of the vehicles. The mathematical model is shown below. The depot is numbered 0, the N destinations are numbered 1, 2..., N, and the K vehicles are numbered 1, 2..., K.

[0020] The objective function in this delivery planning problem, i.e., the total distance traveled, is given by equation (1). The variable X in equation (1) ijk is defined as a binary variable that takes the value 1 when vehicle k moves from destination i to destination j and 0 otherwise.

[0021] The objective function in equation (1) represents the minimization of the total travel distance of all vehicles. Equations (2) to (6) represent the constraints.

[0022]

number

[0023] (Input parameters: constraints) Q: Maximum vehicle load capacity N: A set of delivery destinations K: Set of vehicles (k=1~K) r i : Demand quantity for destination i d ij : Travel distance from delivery destination i (i = 1 to N) to delivery destination j (j = 1 to N, j ≠ i).

[0024] Equations (2) and (3) mean that one vehicle visits each destination only once. Equation (4) limits the total destination demand on any delivery route to less than the vehicle's maximum load capacity. Equations (5) and (6) mean that every vehicle departs from and returns to a depot.

[0025] Input parameters include time constraints such as designated delivery time, travel time, and loading / unloading time, but these are omitted in the above model.

[0026] The values ​​of the variables that minimize the objective function while satisfying these constraints are found. The obtained values ​​of the variables correspond to the desired delivery route.

[0027] Variable X ijk The number of 2 As the number of delivery destinations and vehicles increases, the number of variables also increases accordingly. The number of possible combinations of variables (hereafter sometimes referred to as the search space) increases exponentially as the number of variables increases, making it difficult to solve.

[0028] Therefore, in this embodiment, when observing optimized delivery routes obtained through experiments etc. in the past in delivery planning, it has been empirically found that the majority of vehicle movements are to delivery destinations that are close to each other, and that movements to delivery destinations that are far away are rare. Therefore, a method is considered in which this empirical knowledge is effectively used to reduce the amount of calculation.

[0029] Order of distance from destination i, i.e., d ijThe delivery destination numbers j are sorted in descending order of the value of . The set of numbers that fall within a certain M% exclusion rate (hereinafter simply referred to as M) from the top of the sorted list of j is called j*. The route from i to j* is excluded from the solution search. That is, X ijk = 0(j∈j*) and treat these variables as constants. There are no restrictions on movement from the depot to the destination and from the destination to the depot. That is, X 0jk ,X i0k (i=1~N, j=1~N) will remain variables.

[0030] The method of this embodiment solves a delivery planning problem of delivering packages from a delivery center to N delivery destinations by excluding long-distance routes from the N-1 routes going from a certain delivery destination to the other N-1 delivery destinations in advance at an exclusion rate M and excluding them from the solution search (only a fixed rate m (where m+M=1) of short-distance routes are subject to the solution search).

[0031] This delivery planning method is characterized in that, when delivering packages from one delivery base to N delivery destinations, before calculating the objective function of the above equation (1), the objective function is calculated by first excluding, from among the N-1 routes from one delivery destination to the other N-1 delivery destinations, routes with an exclusion rate M exceeding 0% in descending order of distance, starting from the longest route, as shown in Figure 2, for example.

[0032] By implementing the method of this embodiment, it is possible to reduce the number of variables in the exclusion ratio M%. The solution search space becomes smaller accordingly, reducing the amount of calculation required for the objective function. This effect becomes more pronounced as the value of M is increased. However, increasing M too much will result in a significant restriction on routes. If the excluded routes include an optimal or near-optimal route, the resulting objective function will deviate from the minimum value. Taking these trade-off relationships into consideration, the optimal value of M is determined as appropriate.

[0033] Therefore, in this embodiment, there are no restrictions on movement from the depot to the delivery destination or from the delivery destination to the depot. Therefore, the first delivery destination can be freely selected and determined regardless of the distance. This has the effect of preventing the loss of routes from the depot to delivery destinations that are far away.

[0034] Although this method is limited to routes to nearby destinations, it does not group destinations geographically, so the conventional problem of restricting movement between groups does not arise.

[0035] (Explanation of effect) Numerical calculation experiments were conducted to verify the effectiveness of this method. The scenario was one in which packages were delivered to destinations (number of destinations N = 300) uniformly distributed around a depot. Calculations were performed with the route exclusion rate M set to 0% (no exclusions, before applying this method), 50%, 80%, and 90%. Figure 3 shows the change in the objective function value (total distance traveled) versus calculation time. In this experiment, a heuristic method was used to gradually find a feasible solution. It can be seen that the objective function converges more quickly as the value of the route exclusion rate M is increased. The final objective function value is virtually the same regardless of M. In other words, by applying this method, a solution equivalent to conventional solutions can be obtained in a shorter time. [Example]

[0036] (Second Example) The delivery plan creation method of this embodiment is executed mainly using a route calculation unit FCT, an input parameter storage unit PKP, and an optimal M value storage unit FJP in the delivery plan creation device 10 shown in Fig. 1. The optimal M value storage unit FJP includes a decision unit DCT that compares a set of stored input parameters with newly inputted input parameters and determines the minimum exclusion ratio M according to the newly inputted calculation time limit.

[0037] The delivery plan planning device acquires input parameters to be used by the device from the input unit 13 (or communication unit 15). The route calculation unit FCT receives the input parameters and calculates a delivery route from them. The input parameter storage unit PKP stores input parameters for calculations previously performed. The optimal M value storage unit FJP replies with the optimal M value based on the input parameters and the calculation time limit.

[0038] (Explanation of operation) The operation when a user calculates a delivery route using the delivery plan planning device will be described with reference to FIGS.

[0039] A user provides input parameters (travel distance between delivery destinations, number of trucks, amount of cargo, etc.) and a calculation time limit (upper limit of calculation time) to the delivery plan planning device via input unit 13 (step S1).

[0040] The input parameters given by the user are stored in the input parameter storage unit PKP (step S2). The input parameters stored here are used in the optimum M value calculation, which will be described later.

[0041] The input parameters and calculation time limit given in step S1 are passed to the optimum M value storage unit FJP (step S3).

[0042] The optimum M value storage unit FJP searches an internally stored table using these input parameters and the calculation time limit as keys, and outputs the optimum M value for route calculation (step S4).

[0043] The route calculation unit FCT calculates the route using the input parameters given in step S1 and the M value given in step S4 until the calculation time limit is reached (step S5). The calculation result is returned to the user via the output unit 14 (step S6).

[0044] The operation when updating the table of the optimum M value storage unit FJP will be described with reference to FIG.

[0045] This operation is assumed to be performed during times when the user is not using the device. The input parameter history used in past calculations is retrieved from the input parameter storage unit PKP (step S11). Route calculation is performed using these input parameters (step S12). At this time, the M value is set to multiple appropriate values ​​between 0% and 100%, and the calculation is repeated. A large number of current solutions (total distance traveled) versus calculation time are recorded (step S13). In other words, the total distance traveled result of the objective function shown in Figure 3 is obtained. The calculation start time for these changes in total distance traveled as shown in Figure 3 is aligned, for example, as shown on the right in Figure 6, and the calculation time is scanned and mapped to the change in total distance traveled versus the M value, as shown on the left in Figure 6. From the results shown on the left in Figure 6, the M value that minimizes the total distance traveled at each calculation time is set as the optimal M value, and the table in the optimal M value storage unit FJP is updated (step S14). In this way, the optimal M value is calculated in step S14.

[0046] In this way, the delivery plan planning device 10 performs in advance a plurality of trial calculations to minimize the objective function using a plurality of exclusion ratios for each set of input parameters of the objective function, and the optimal M value storage unit FJP stores the value of the exclusion ratio that minimizes the total travel distance for each calculation time for each set of input parameters in association with each set of input parameters, and compares the stored set of input parameters with newly input parameters to determine the minimum exclusion ratio exceeding 0% according to the newly input calculation time limit (determination unit DCT). In other words, when the user performs a delivery plan calculation, the value of M is determined by searching (comparing) an optimal M value table calculated in advance using past calculation history for one that is close to the input conditions for the current calculation.

[0047] (Explanation of effect) When a user repeatedly uses this device to calculate a delivery plan, the device can retrieve the optimal M value from the optimal M value storage unit FJP and automatically calculate using a value of M that is close to the optimal value. In other words, it becomes possible to create a better plan and provide a response in a short calculation time. [Explanation of symbols]

[0048] 10 Delivery planning device FCT Route Calculation Unit PKP Input parameter storage unit FJP optimal M value storage section DCT decision section

Claims

1. A delivery planning method using a delivery planning device to create a traveling route that minimizes an objective function that formulates the sum of the total travel distances of a vehicle from a delivery base to travel the travel distances of a route between delivery destinations and return to the delivery base, When delivering packages from one delivery base to N delivery destinations, before creating a circular route, the total number of N-1 routes from one delivery destination to the other N-1 delivery destinations is set to 100%, the routes are arranged in descending order of travel distance starting from the longest route, and an exclusion percentage M % of multiple routes to be excluded in order from the longest route is set, The route with the exclusion rate M% is excluded in advance so that it is not included in the route creation. A delivery plan creation method characterized by calculating the objective function and creating a tour route.

2. A delivery planning device that creates a travel route that minimizes an objective function that formulates the sum of the total travel distances of a vehicle from a delivery base to the delivery base, traveling the travel distances of a route between delivery destinations, and returning to the delivery base, When delivering packages from one delivery base to N delivery destinations, before creating a circular route, the delivery plan creation device is characterized by comprising a route calculation unit that sets the total number of N-1 routes from one delivery destination to the other N-1 delivery destinations to 100%, arranges the routes in descending order of travel distance starting from the longest route, sets an exclusion percentage M% of multiple routes to be excluded in order from the longest route, and excludes routes with the exclusion percentage M% in advance so that they are not included in the creation of the circular route, and calculates the objective function to create the circular route.

3. A delivery planning device as described in claim 2, characterized in that it comprises an optimal M value storage unit that performs multiple trial calculations of the objective function for each of the multiple exclusion percentages M%, scans the change in the objective function for each exclusion percentage M% relative to the calculation time of the objective function, and stores the value of the exclusion percentage M% that minimizes the total driving distance for each calculation time as an optimal M value.

4. A delivery planning device as described in Claim 3, characterized in that when a calculation limit time for calculating the objective function is input to the delivery planning device, the optimal M value corresponding to the calculation limit time is output.

5. A delivery planning device as described in claim 4, characterized in that the objective function is calculated using the optimal M value until the calculation time limit is reached.

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