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Logistics transportation route scheduling decision-making method and device and storage medium

A decision-making method and logistics technology, applied in logistics, complex mathematical operations, instruments, etc., can solve the problems of difficult real-time monitoring of garbage volume, regardless of the frequency of visits to each node, and the inability to solve optimization schemes, etc., to improve periodic optimization and reduce waste. The effect of calculation volume

Pending Publication Date: 2021-06-08
上海泰聚数据技术有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Considering that the generation rate of garbage is relatively stable, and the amount of garbage is difficult to realize real-time monitoring, fixed transportation routes and periodic scheduling are more suitable. However, the existing technology applications are often only for short-term route optimization. It does not involve long-term, and does not consider the frequency of visits to each node, but once the period is put into it, since this type of problem is a large-scale nonlinear problem, it cannot be solved to obtain an optimal solution

Method used

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  • Logistics transportation route scheduling decision-making method and device and storage medium
  • Logistics transportation route scheduling decision-making method and device and storage medium
  • Logistics transportation route scheduling decision-making method and device and storage medium

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0055] Such as figure 1 As shown, this embodiment provides a logistics transportation route scheduling decision-making method, including:

[0056] S1: Obtain the logistics node set N of the target task vehicle and the visit frequency ρ of each node in the logistics node set N i ;

[0057] S2: Construct a path set R according to the round-trip path from warehouse node 0 in the logistics node set N to other logistics nodes in the logistics node set N; while constructing the path set R, use mTSP or traditional TSP for it Algorithm for preliminary solution;

[0058] S3: Construct the main problem model V according to the path set R m ; The main problem model V m for Among them, the f k is the flow of path k; V k is the cost of path k; where, To meet the conditions: is whether node i is visited in path k; ρi is the number of visits to logistics node i; specifically, f k It is the continuous numeric usage frequency of path k. Since it can be a decimal in the optimizat...

Embodiment 2

[0073] Such as figure 1 As shown, this embodiment provides a logistics transportation line scheduling decision-making method, which is based on the logistics transportation line scheduling decision-making method described in Embodiment 1, and is applied when the operation optimization model of the target operating vehicle is When, among them, C ij is the cost from logistics node i to logistics node j, x kij In the path k, whether the path (i, j) is selected; ρ 1 is the visit frequency of node 1.

[0074] That is to say, the method described in Embodiment 1 is applied to light-load situations where the transportation has strong periodicity, and the transportation load generally constitutes a condition that needs to be considered.

[0075] That is to say, when the optimization model of the target operating vehicle is When , the algorithm of S1-S10 can achieve a better implementation effect, but due to is unsolvable, so use S1-S10 to obtain the optimization result. Of co...

Embodiment 3

[0079] This embodiment provides an electronic device, including a processor, a memory, and a computer program stored in the memory and operable on the processor. The processor is used to execute the computer programs stored in the memory. The program realizes the method for scheduling decision-making of logistics transportation routes described in Embodiment 1.

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Abstract

The invention discloses a logistics transportation route scheduling decision-making method and device and a storage medium. The method comprises the steps of obtaining a logistics node set N of a target task vehicle and an access frequency rho i of each node in the logistics node set N; constructing a path set R according to a back-and-forth path from the warehouse node 0 in the logistics node set N to other logistics nodes in the logistics node set N; constructing a main problem model Vm according to the path set R; acquiring a dual variable Wi according to the main problem model Vm; constructing a new sub-problem model Vs according to the dual variable Wi; optimizing the sub-problem model to obtain an optimized path sequence; constructing an optimized path according to the optimized path sequence and adding the optimized path into the path set R; judging whether the sub-problem model Vs is smaller than or equal to 0, if yes, outputting a path set R, and if not, continuing to constructing a main problem model Vm according to the path set R; and transmitting the path set R to the target task vehicle to control the operation of the vehicle. The technical effect is that the logistics operation cost is the lowest in an infinitely long operation time range.

Description

technical field [0001] The invention relates to the field of logistics transportation, in particular to a method, device and storage medium for scheduling decision-making of logistics transportation routes. Background technique [0002] For logistics companies engaged in transportation tasks such as distribution or recycling, if they can have a relatively fixed transportation route and task cycle, it can greatly facilitate operation and management. Sometimes, fixed-line transportation is not suitable, for example, the customer's order may vary greatly from day to day. Other times, fixed lines become possible. [0003] Taking garbage recycling as an example, the garbage management company needs to send vehicles to various garbage collection points at regular intervals to collect the garbage back to the storage point. Considering that the generation rate of garbage is relatively stable, and the amount of garbage is difficult to realize real-time monitoring, fixed transportat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q10/08G06F17/11
CPCG06Q10/047G06Q10/083G06F17/11
Inventor 孙磊闫明李彤
Owner 上海泰聚数据技术有限公司