Solving traveling salesman problems using generalized chromosome genetic algorithm

被引：48
|
作者：
Yang, Jinhui [1 ]
Wu, Chunguo [1 ,2 ]
Lee, Heow Pueh [3 ,4 ]
Liang, Yanchun [1 ]
机构：
[1] Jilin Univ, Coll Comp Sci & Technol, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun 130012, Peoples R China
[2] Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
[3] Inst High Performance Comp, Singapore 117528, Singapore
[4] Natl Univ Singapore, Dept Mech Engn, Singapore 117576, Singapore
来源：
PROGRESS IN NATURAL SCIENCE-MATERIALS INTERNATIONAL | 2008年 / 18卷 / 07期
基金：
中国国家自然科学基金;
关键词：
chromosome; genetic algorithm; solution space; generalized traveling salesman problem;
D O I：
10.1016/j.pnsc.2008.01.030
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Generalized chromosome genetic algorithm (GCGA) was proposed for solving generalized traveling salesman problems (GTSP) as reported in the authors' earlier work. Theoretically, the GCGA could also be used to solve the classical traveling salesman problem (CTSP), which has not been reported by others. In this paper, the generalized chromosome characteristics are analyzed and the feasibility for consistently solving the GTSP and CTSP is verified. Numerical experiments show the advantages of the GCGA for solving a largescale CTSP. (c) 2008 National Natural Science Foundation of China and Chinese Academy of Sciences. Published by Elsevier Limited and Science in China Press. All rights reserved.
引用
收藏
页码：887 / 892
页数：6
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