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基于最优保留的CGA及其在TSP欺骗问题中的应用
引用本文:武晓今,朱仲英. 基于最优保留的CGA及其在TSP欺骗问题中的应用[J]. 微型电脑应用, 2005, 21(4): 43-45,57
作者姓名:武晓今  朱仲英
作者单位:上海交通大学自动化系
摘    要:本文在对CGA算法分析说明的基础上,运用改进CGA的方法来解决TSP欺骗问题。虽然CGA能够“快速、简单”的解决一些优化问题,但是由于其概率向量中基因的独立性,使得它在进化计算中会丢失基因之间的关联信息,从而可能无法解决如欺骗函数等复杂、困难问题。文中通过对CGA在TSP算法上的改进,以一定遗传尺度保留竞争最优个体,从而有效地解决TSP欺骗问题,并通过仿真结果验证了该算法,给出解决该类组合优化问题的一个有效例证。

关 键 词:CGA  TSP欺骗问题  局部最优  全局最优
文章编号:1007-757X(2005)04-0043-03

CGA Based on Optimum Retention and Its Application in TSP Deceptive Problems
Wu Xiaojing,Zhu Zhongying. CGA Based on Optimum Retention and Its Application in TSP Deceptive Problems[J]. Microcomputer Applications, 2005, 21(4): 43-45,57
Authors:Wu Xiaojing  Zhu Zhongying
Abstract:This paper illustrates and analyzes the Compact Genetic Algorithm (CGA) and proposes to use the improved CGA to solve TSP deceptive problems. Though CGA can"quickly and simply"solve some optimal problems, the operation of each gene is independent, which may lose linkage information, thus not being able to solve such difficult and complex problems as deceptive fuction. This article improves the CGA algorithm in TSP to solve the decetive problems effectively and its performance has been verified by emulation results, which can also be used to solve similar combinational optimization problems.
Keywords:CGA TSP deceptive problems local optimum global optimum  
本文献已被 CNKI 维普 万方数据 等数据库收录!
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