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基于粒子群算法的并行多机调度问题研究
引用本文:刘志雄,王少梅.基于粒子群算法的并行多机调度问题研究[J].计算机集成制造系统,2006,12(2):183-187,296.
作者姓名:刘志雄  王少梅
作者单位:武汉科技大学,机械自动化学院,湖北,武汉,430081;武汉理工大学,物流工程学院,湖北,武汉,430063;武汉理工大学,物流工程学院,湖北,武汉,430063
摘    要:将港口拖轮作业调度问题描述为一类带特殊工艺约束的并行多机调度问题,采用粒子群算法求解该类调度问题,提出了一种2维粒子表示方法,通过对粒子位置向量进行排序生成有效调度,并采用粒子位置向量多次交换的局部搜索方法来提高算法的搜索效率。最后,通过计算验证了混合粒子群算法的有效性。

关 键 词:粒子群算法  并行多机调度  特殊工艺约束  港口拖轮调度
文章编号:1006-5911(2006)02-0183-05
收稿时间:2004-11-22
修稿时间:2004-11-222005-01-17

Research on parallel machines scheduling problem based on particle swarm optimization algorithm
LIU Zhi-xiong,WANG Shao-mei.Research on parallel machines scheduling problem based on particle swarm optimization algorithm[J].Computer Integrated Manufacturing Systems,2006,12(2):183-187,296.
Authors:LIU Zhi-xiong  WANG Shao-mei
Abstract:Port tugboat operation scheduling is regarded as parallel machines scheduling problem with special process constraint. Particle swarm optimization algorithm was used to solve the scheduling problem. The two-dimensional particle representation of parallel machines scheduling was proposed, and valid scheduling was generated by sequencing position vectors of particles. The local search approach of repeated interchanges of the particle position vectors was proposed to improve search efficiency. Finally the hybrid particle swarm algorithm was validated by computation.
Keywords:particle swarm optimization algorithm  parallel machines scheduling  special process constraint  port tugboat scheduling
本文献已被 CNKI 维普 万方数据 等数据库收录!
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