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基于改进粒子群算法的离子膜车间调度问题研究
引用本文:周明,王万良,徐新黎,介婧.基于改进粒子群算法的离子膜车间调度问题研究[J].控制与决策,2010,25(7):1021-1025.
作者姓名:周明  王万良  徐新黎  介婧
作者单位:1. 浙江工业大学,计算机科学与技术学院,杭州,310023
2. 浙江工业大学,信息工程学院,杭州,310023
基金项目:国家863计划项目,国家自然科学基金,浙江省自然科学基金
摘    要:针对某电化厂离子膜车间的调度问题,以产值最大化为目标函数,建立具有中间存储的连续和批处理过程相结合的多产品多批次调度模型.提出一种改进的粒子群算法(IPSO),加入自适应混沌变异操作,在加强算法局部搜索能力的同时保证搜索过程中种群的多样性,并利用IPSO对建立的模型进行求解.仿真结果表明了模型和算法的有效性,在满足计划的前提下,获得了满意的日生产总值.

关 键 词:粒子群算法  混沌变异  离子膜车间  中间存储
收稿时间:2009/7/6 0:00:00
修稿时间:2009/9/7 0:00:00

Research of ion exchange membranes shop scheduling problem based on improved PSO
WANG Wan-liang,ZHOU Ming,XU Xin-li,JIE Jing.Research of ion exchange membranes shop scheduling problem based on improved PSO[J].Control and Decision,2010,25(7):1021-1025.
Authors:WANG Wan-liang  ZHOU Ming  XU Xin-li  JIE Jing
Abstract:The paper develops a multi-product and multi-batch scheduling model for the ion exchange membranes shop
scheduling problem of certain electro-chemical plant firstly, which aims at maximize production value and mixes middle-
storage combination of continuous and batch processes. Then an improved particle swarm optimization (IPSO) algorithm
is introduced to solve the special shop scheduling problem, which takes advantage of adaptive chaos mutation operator to
enhance the local search ability and keep the swarm diversity. Finally, the result of simulation shows that, the model and the
algorithm are effective, which not only meet the plan demands, but also get satisfactory of day-production value.
Keywords:Particle swarm optimization algorithm|Chaos mutation|Ion exchange membranes shop|Middle-storage
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