陕西师范大学学报（自然科学版）Issue(6)：36-42,7.DOI:10.15983/j.cnki.jsnu.2015.06.263
加速度粒子群算法在多旅行商问题中的应用
Application of a new acceleration particle swarm optimization for solving multiple traveling salesman problems
摘要
Abstract
To overcome the premature convergence of the standard particle swarm optimization (PSO)in solving multiple travelling salesman problems (MTSP),a new acceleration particle swarm optimization is constructed.Rely on the idea of mechanics,the movement of particle is de-scribed as search motion driving by force in solution space.The particle is attracted by personal best force,global best force and repelled by local best force.Thus the acceleration of particle de-pends on the resultant of forces.Using convergence criterions to estimate premature conver-gence,the local best will repel all the particles when premature convergence occurs,so the parti-cle swarm can jump out the local best and continue to search.In order to improve the efficiency of the algorithm,a dimensional learning strategy of particle and a new coding method are designed for MTSP.The simulation results show that the proposed algorithm can effectively overcome the premature convergence,and improve the quality and stability of solutions.Thus it provides a fea-sible method for MTSP.关键词
多旅行商问题/粒子群算法/学习策略/编解码方法Key words
multiple traveling salesman problems/particle swarm optimization/learning strate-gy/coding method分类
信息技术与安全科学引用本文复制引用
强宁,康凤举..加速度粒子群算法在多旅行商问题中的应用[J].陕西师范大学学报（自然科学版）,2015,(6):36-42,7.基金项目
船舶预研支撑技术基金（11J4．1．1）；水下信息处理与控制国家重点实验室基金 （）
