Study on the Improvement of Genetic Algorithm by Using Vehicle Routing Problem

被引：1

作者：

Guo Meini ^{[1
]}

机构：

[1] Xian Phys Educ Univ, Xian 710068, Shaanxi Provinc, Peoples R China

来源：

MACHINE DESIGN AND MANUFACTURING ENGINEERING II, PTS 1 AND 2 | 2013年 / 365-366卷

关键词：

VRP; Genetic algorithms; Initial population; Parthenon genetic algorithm;

D O I：

10.4028/www.scientific.net/AMM.365-366.194

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Improve the existing genetic algorithm, make the vehicle path planning problem solving can be higher quality and faster solution. The mathematic model for study of VRP with genetic algorithms was established. An improved genetic algorithm was proposed, which consist of a new method of initial population and partheno genetic algorithm revolution operation. Exploited Computer Aided Platform and Validated VRP by simulation software. Compared this improved genetic algorithm with the existing genetic algorithm and approximation algorithms through an example, convergence rate Much faster and the Optimal results from 117.0km Reduced to 107.8km,proved that this article improved genetic algorithm can be faster to reach an optimal solution. The results showed that the improved GA can keep the variety of cross and accelerate the search speed.

引用

页码：194 / 198

页数：5