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。
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.
出处
《计算机工程与设计》
CSCD
北大核心
2007年第19期4738-4740,共3页
Computer Engineering and Design
