计算机应用研究2011，Vol.28Issue(4)：1276-1278,1282,4.DOI:10.3969/j.issn.1001-3695.2011.04.021
基于混沌自适应变异粒子群算法的铁路空车调配
Railway empty car distribution problem based on chaos adaptive mutation particle swarm optimization
摘要
Abstract
It is very difficult to find an optimal solution for an actual large-scale empty car distribution problem.To solve this problem, proposed a chaos adaptive mutation particle swarm optimization algorithm.In the algorithm, enhanced the diversity of the particle swarm by using the ergodicity of the chaos to initialize the swarm, and adjusted the mutation probability by variance of the population' s fitness at each iteration, improved the capability of local and global search by introducing an adaptive inertia weighting factor for each particle to adjust its inertia weight factor adaptively in response to its fitness.Investigated the algorithm of chaos adaptive mutation particle swarm algorithm to solve railway empty car distribution problem, established the mathematic mode which minimized total distance of empty car and developed the solution algorithm.Numerical simulation results of solving railway empty car distribution problem verify that the optimum result and searching performance of chaos adaptive mutation particle swarm optimization algorithm is better than that of ACO and PSO.关键词
粒子群算法/混沌自适应变异/铁路空车调配Key words
particle swarm optimization(PSO)/ chaos adaptive mutation/ railway empty car distribution分类
信息技术与安全科学引用本文复制引用
王铁君,邬月春..基于混沌自适应变异粒子群算法的铁路空车调配[J].计算机应用研究,2011,28(4):1276-1278,1282,4.基金项目
国家自然科学基金资助项目(10972095) （10972095）
甘肃省自然科学基金资助项目(2008GS02601) （2008GS02601）
