置换流水车间调度粒子群算法与参数设置分析被引量：2

Particle Swarm Optimization and Parameter Setting Analysis for Permutation Flow Shop Scheduling Problem

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摘要针对置换流水车间调度问题,在介绍了基于粒子位置次序的粒子群算法二维编码方法之后,采用惯性权重线性递减粒子群算法对置换流水车间调度问题进行了优化.在此基础上,对粒子群算法的相关参数设置问题展开分析,主要针对惯性权重的取值、粒子群种群数量、粒子位置和速度的初始化以及粒子位置和速度的限制范围等几个方面展开实验研究.粒子群算法的参数设置分析将有助于提高求解置换流水车间调度问题的粒子群算法优化效率和优化性能. After the two-dimension encoding based on the particle position sequence of particle swarm optimization algorithm for permutation flow shop scheduling is introduced,the linearly decreasing inertia weight particle swarm optimization is employed to optimize the permutation flow shop scheduling problem.Moreover,parameter setting of particle swarm optimization algorithm for the permutation flow shop scheduling is analyzed through the experiment and the parameters which comprising of the inertia weigh,swarm population,initialization of the particle and limitation of the particle.The analysis of parameter setting can improve the optimization efficiency and performance of particle swarm optimization for the permutation flow shop scheduling.

作者刘志雄严新平赵润军

机构地区武汉科技大学机械自动化学院天津港(集团)有限公司博士后科研工作站武汉理工大学水路公路交通安全控制与装备教育部工程研究中心

出处《武汉理工大学学报（交通科学与工程版）》 2010年第6期1129-1132,1137,共5页 Journal of Wuhan University of Technology（Transportation Science & Engineering）

基金国家自然科学基金项目(批准号:70801047) 中国博士后科研基金项目(批准号:20090450769) 湖北省教育厅科学技术研究计划优秀中青年人才项目(批准号:Q20101115)资助

关键词粒子群算法置换流水车间调度参数设置实验分析 particle swarm optimization algorithm permutation flow shop scheduling parameter setting empirical analysis

分类号 TP301.6 [自动化与计算机技术—计算机系统结构]

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