Multi-vehicle vehicle route optimization method, server and system

A technology for optimizing server and vehicle routing, applied in the field of multi-model vehicle routing optimization, can solve problems such as premature convergence of the algorithm and easy to fall into local optimum, and achieve the effect of enhancing local search ability, better convergence speed, and faster optimization speed

Inactive Publication Date: 2019-01-11
SHANDONG UNIV
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

Studies have shown that the convergence of the GSA algorithm is significantly better than other intelligent optimization algorithms such as PSO and GA, but the proposed algorithms all have problems such as premature convergence and easy to fall into local optimum.

Method used

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  • Multi-vehicle vehicle route optimization method, server and system
  • Multi-vehicle vehicle route optimization method, server and system
  • Multi-vehicle vehicle route optimization method, server and system

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Embodiment Construction

[0065] It should be pointed out that the following detailed description is exemplary and intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0066] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combinations thereof.

[0067] Such as Figure 5 As shown, a kind of multi-model vehicle route optimization method of the present inven...

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Abstract

The invention discloses a multi-vehicle vehicle route optimization method, a server and a system. The multi-vehicle vehicle route optimization method comprises the steps of: 1. constructing a vehiclerouting optimization model of multiple vehicle type; 2, solving a vehicle route optimization model of multiple vehicle types; mapping the particle position in the gravitational search algorithm to thecustomer point sequence, and assigning the vehicle to the customer point. The crossover operator and mutation operator of genetic algorithm are introduced in the gravitational search algorithm. If the crossover operator and mutation operator are better than the original particle fitness value, the position of the particle is updated. When the maximum number of iterations is reached, the optimal solution is output.

Description

technical field [0001] The invention belongs to the field of distribution route optimization, and in particular relates to a multi-model vehicle route optimization method, server and system. Background technique [0002] Distribution plays an important role in logistics and supply chain. The driving path of delivery vehicles can be modeled as a vehicle routing problem (Vehicle Routing Problem, VRP). VRP plays an important role in optimizing the logistics distribution network and reducing the cost of logistics distribution, and is considered to be one of the most important combinatorial optimization problems. In real life, companies often need to arrange vehicles of different sizes or loads to complete the delivery together. At this time, the VRP problem can be abstracted into a multi-vehicle routing problem (Fleet Size and Mix Vehicle Routing Problem, FSMVRP). FSMVRP is an important variant of the VRP problem, where the fleet consists of vehicles with different loads and c...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/08G06Q10/04G06N3/12
CPCG06N3/126G06Q10/047G06Q10/08355Y02T10/40
Inventor 王艳艳刘晴胡金昌赵晓峰赵宛梦
Owner SHANDONG UNIV
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