Hybrid Evolutionary Algorithm for the Vehicle Routing Optimization Problem

被引：0

作者：

Yang, Xi-quan ^{[1
]}

Zhou, Jian-yuan ^{[1
]}

Cheng, Na

Cao, Xue-ya ^{[1
]}

机构：

[1] NE Normal Univ, Sch Comp Sci, Changchun 130024, Jilin, Peoples R China

来源：

2008 INTERNATIONAL WORKSHOP ON INFORMATION TECHNOLOGY AND SECURITY | 2008年

关键词：

vehicle routing problem; genetic algorithm; immune algorithm; pareto optimal solutions;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new hybrid evolutionary algorithm (HEA) is proposed in the paper by combining the genetic algorithm, immune algorithm, ant colony optimization and Pareto optimal solutions. The HEA has high convergence precision and improved the diversity of population. Multiple near optimization paths can be developed by the algorithm with multi-objective restriction, and satisfy to minimize the routing of transportation and the numbers of the vehicles. The HEA has been used to solve the vehicle routing problem, the results of simulation experiment show that the HEA can gain higher global convergence rate and higher speed.

引用

页码：188 / 191

页数：4

共 6 条

[1]

Dan Zhenggang, 2006, Journal of Tsinghua University (Science and Technology), V46, P1945

[2]

JIANG LM, 2006, COMPUTER APPL SOFTWA, V23, P95

[3]

Tang K., 2002, J DONGHUA U NATURAL, V28, P66

[4]

Wu Zong-yan, 2006, Computer Engineering and Applications, V42, P11

[5]

YANG XQ, CONSTRUCTING XML IND, P32

[6] Approach of constructing multi-objective Pareto optimal solutions using arena's principle [J].

Zheng, Jin-Hua ;

Jiang, Hao ;

Kuang, Da ;

Shi, Zhong-Zhi .

Ruan Jian Xue Bao/Journal of Software, 2007, 18 (06) :1287-1297

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