[1]徐 鹏,王 雷,张文义.遗传算法求解VRP的种群初始化改进[J].南京师范大学学报(工程技术版),2009,09(03):070-74.
　Xu Peng,Wang Lei,et al.Improvement on Population Initialization of Genetic Algorithm Solution for VRP[J].Journal of Nanjing Normal University(Engineering and Technology),2009,09(03):070-74.
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遗传算法求解VRP的种群初始化改进
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南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
09卷
期数:
2009年03期
页码:
070-74
栏目:
出版日期:
2009-09-30

文章信息/Info

Title:
Improvement on Population Initialization of Genetic Algorithm Solution for VRP
作者:
徐 鹏1;  2;  王 雷1;  张文义1
1. 河海大学交通学院, 江苏南京210098;
2. 河海大学海岸灾害及防护教育部重点实验室, 江苏南京210098
Author(s):
Xu Peng1; 2; Wang Lei1; Zhang Wenyi1
1.College of Traffic,Hohai University,Nanjing 210098,China;2.Key Laboratory of Coastal Disaster and Defence,Hohai University,Nanjing 210098,China
关键词:
VRP;  初始种群;  遗传编码;  遗传算法;  改进遗传算法
Keywords:
VRP;  initial popu la tion;  genetic coding;  genetic a lgo rithm;  improved genetic algor ithm
分类号:
TP18
摘要:
传统的遗传算法求解VRP时,初始种群多半采取随机生成法形成染色体方案,以致于迭代开始就可能形成许多不可行的方案,要进行大量的计算后才能得到优化的方案,这在很大程度上降低了算法的运算效率.论文提出的遗传编码策略,对初始种群给予基于知识型启发策略,使得初始种群一开始就表现为一种较优的状态.
Abstract:
W hen trad itiona l Genetic A lgor ithms( GA ) w as applied in VRP, mo st of the in itia l population genera te the chrom osom e prog ram by tak ing a random m ethod, which leads to a lo t o f infeasib le schem es in the beg inning, and a g reat dea l o f ca lculations be fore obta ining an optim ize one. Th is reduced the ca lcu lating effic iency o f the a lgor ithm to the g reat extent. The g enetic cod ing strategy, propo sed by the pape r, g iv es in itia l population a know ledge-based heuristic strategy, w hich m akes in itial popu la tion a better perfo rmance at the very start.

参考文献/References:

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备注/Memo

备注/Memo:
基金项目: 河海大学自然科学基金( 2008429911 )资助项目.
通讯联系人: 徐 鹏, 博士研究生, 讲师, 研究方向: 智能交通系统、物流系统优化. E-mail:rob inxp@ sina. com
更新日期/Last Update: 2013-04-23