Improved Quantum Genetic Algorithm for Solving TSP

被引：0

作者：

Li XiaoBo ^{[1
]}

机构：

[1] Weifang Univ, Sch Comp & Commun Engn, Weifang, Peoples R China

来源：

2011 AASRI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INDUSTRY APPLICATION (AASRI-AIIA 2011), VOL 2 | 2011年

关键词：

Quantum Genetic Algorithm; TSP; improved;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

General Quantum Genetic Algorithm(QGA) havn't the crossover operations, easy to fall into local optimum. For sovling TSP, the improved Quantum Genetic Algorithm can avoid the occurrence of local optimum for using crossover operation in the paper;Otherwise,the adjusting method of the rotation angle have nothing to do with the problem so it have better adaptability in solving TSP. The improved QGA, which controlls the hybrid process through setting hybrid threshold and hybrid probability in the quantum hybrid process, maintains population multiple well at the same time speed up population's convergence rate. The experiment proves this improved QGA have the features of small population scale and quick contraction speed,and can well solve the TSP.

引用

页码：79 / 82

页数：4