一种新型自适应混沌粒子群算法在联盟运输调度问题中的研究  

Selfadaptive Chaos Particle Swarm Optimization for Allied Vehicle Routing Problems

作　　者：蔡延光[1] 魏明[1] 

机构地区：[1]广东工业大学自动化学院,广东广州510090

出　　处：《系统工程》2008年第8期32-36,共5页Systems Engineering

基　　金：国家自然科学基金资助项目(60374062);广东省自然科学基金团队资助项目(8351009001000002);广东省科技计划项目(2007B010200070)

摘　　要：提出了一种新的自适应混沌粒子群优化算法。该算法在运行过程中根据群体适应度方差和最优解的大小确定当前最佳粒子引入混沌搜索有效位置的概率,有效结合粒子群全局和混沌局部搜索,避免了基本粒子群优化算法易于陷入局部最优的缺点,提高了进化后期算法的收敛精度。将该算法用于解决联盟运输调度问题,实验结果表明该算法具有较好的性能。We present a new adaptive chaos particle swarm optimization algorithm, during the calculating process of which the probability for the current best particle to search the effective position by intoducing chaos is determined by the variance of the population＇s fitness and the current ooptimal solution. By combinning PSO with the chaotic partial searching, the proposed algorithm can void local optimum caused by basic particle swarm optimization algorithm and improve the accurancy in the later evolution period compared with original PSO. The application of this method to allied vehicle routing verifies its effectiveness

关 键 词：联盟运输调度 混沌 粒子群算法 

分 类 号：TP301[自动化与计算机技术—计算机系统结构] U116[自动化与计算机技术—计算机科学与技术]