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基于QPSO方法优化求解TSP
引用本文:李盘荣,须文波.基于QPSO方法优化求解TSP[J].计算机工程与设计,2007,28(19):4738-4740.
作者姓名:李盘荣  须文波
作者单位:1. 江南大学,信息工程学院,江苏,无锡,214036;无锡广播电视大学,江苏,无锡,214021
2. 江南大学,信息工程学院,江苏,无锡,214036
摘    要:针对粒子群优化算法PSO求解旅行商问题TSP收敛速度不够快的缺陷,提出利用量子粒子群优化算法QPSO求解TSP,在交换子和交换序概念的基础上,以Matlab语言为开发工具实现了TSP最佳路径的求解.实验表明改造QPSO算法用于优化求解14点的TSP,能够迅速得到最优解,收敛速度加快,搜索效率得到较大水平提高;QPSO方法在求解组合优化问题中将非常有效.

关 键 词:粒子群优化算法  量子粒子群优化算法  优化  旅行商问题  组合优化  方法  优化求解  based  problems  优化问题  组合  水平  搜索效率  最优解  算法  改造  实验  路径  最佳  工具实现  开发  语言  Matlab  交换序  交换子
文章编号:1000-7024(2007)19-4738-03
修稿时间:2006-11-25

Solve traveling salesman problems based on QPSO
LI Pan-rong,XU Wen-bo.Solve traveling salesman problems based on QPSO[J].Computer Engineering and Design,2007,28(19):4738-4740.
Authors:LI Pan-rong  XU Wen-bo
Affiliation:1.School of Information Technology, Southern Yangtze University, Wuxi 214036, China; 2. Wuxi Radio and Television University, Wuxi 214021, China
Abstract:The algorithm of quantum particle swarm optimization(QPSO) is developed to solve traveling salesman problems(TSP).This algorithm increase the speed of convergence instead of the basic algorithm of particle swarm optimization(PSO).Based on the con-cepts of swap operator and swap sequence,TSP is solved as fast as possible with Matlab.The experiments show that the improved QPSO,which is practised to a traveling salesman problem with 14 nodes,can reach the best results quickly and improve the level of searching efficiency.Therefore QPSO will help to solve the problems of combinatorial optimization effectively.
Keywords:PSO algorithm  QPSO algorithm  optimize  traveling salesman problems  combinatorial optimization
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