| 基于改进粒子群算法的车间作业排序的优化设计 |
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| 引用本文： | 黄慧,黎向锋,左敦稳,薛善良.基于改进粒子群算法的车间作业排序的优化设计[J].中国制造业信息化,2011,40(21). |
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| 作者姓名： | 黄慧 黎向锋 左敦稳 薛善良 |
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| 作者单位： | 南京航空航天大学机电学院,江苏南京,210016 |
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| 摘 要： | 兼顾车间作业排序中的制造周期和机器利用率,建立了以最小化最大完工时间为主目标、以最大化机器利用率为从目标的优化模型。设计了引入自适应技术的惯性权重,使基本粒子群算法的学习因子可动态变化地改进粒子群算法,并用该改进后的算法对车间作业排序进行了优化设计。实例研究表明:改进后的粒子群算法在收敛速度和收敛可靠性上均优于未改进的粒子群算法,在求解车间作业排序问题的应用中具有更高的求解质量。
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| 关 键 词： | 车间作业排序 自适应技术 粒子群算法 |
Design of Job Shop Scheduling Based on Improved Particle Swarm Algorithm |
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| HUANG Hui,LI Xiang-feng,ZUO Dun-wen,XUE Shan-liang.Design of Job Shop Scheduling Based on Improved Particle Swarm Algorithm[J].Manufacture Information Engineering of China,2011,40(21). |
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| Authors: | HUANG Hui LI Xiang-feng ZUO Dun-wen XUE Shan-liang |
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| Affiliation: | HUANG Hui,LI Xiang-feng,ZUO Dun-wen,XUE Shan-liang(Nanjing University of Aeronautics & Astronautics,Jiangsu Nanjing,210016,China) |
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| Abstract: | Aiming at the changes of manufacturing cycle and machine availability,it establishes an optimization model to minimize the maximum completion time and maximize the machine availability,designs an improved particle swarm optimization.This optimization includes the adaptive technology and the dynamic learning factor.The improved particle swarm optimization is used for a optimum design of job shop scheduling.The application shows that the improved particle swarm optimization is much better than the standard PS... |
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| Keywords: | Job Shop Scheduling Adaptive Technology Particle Swarm Algorithm |
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