| 混合粒子群算法在job-shop动态调度中的应用 |
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| 引用本文： | 王策,王书锋,冯冬青,梁燕.混合粒子群算法在job-shop动态调度中的应用[J].计算机工程与应用,2010,46(26):219-222. |
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| 作者姓名： | 王策 王书锋 冯冬青 梁燕 |
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| 作者单位： | 郑州大学 电气工程学院，郑州 450001 |
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| 摘 要： | 提出了基于事件驱动的动态调度策略，以融合遗传算法的粒子群算法来实现作业车间生产调度，有很好的收敛精度；在此基础上，对作业车间生产调度中的工件增加及取消、机器故障等各种动态事件进行了研究，能在扰动后提供新的调度计划，有效地解决了车间动态调度的一致性和连续性的问题。
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| 关 键 词： | 作业车间生产调度 粒子群算法 遗传算法 动态事件 |
| 收稿时间： | 2009-2-23 |
| 修稿时间： | 2009-4-9
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Application of hybrid PSO in job-shop dynamic scheduling problem |
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| WANG Ce,WANG Shu-feng,FENG Dong-qing,LIANG Yan.Application of hybrid PSO in job-shop dynamic scheduling problem[J].Computer Engineering and Applications,2010,46(26):219-222. |
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| Authors: | WANG Ce WANG Shu-feng FENG Dong-qing LIANG Yan |
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| Affiliation: | Department of Electrical Engineering，Zhengzhou University，Zhengzhou 450001，China |
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| Abstract: | A new event-driven strategy of dynamic scheduling has been introduced in this paper.The particle swarm optimization which combining a genetic algorithm is used in the job shop scheduling, which has a good astringency.The dynamic events which concerning machine,job and examination have been researched in this paper and a new plan can be provided by part-renovating ,which can solve the problem of consistency and continuity in dynamic scheduling. |
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| Keywords: | job shop scheduling problem particle swarm optimization genetic algorithm dynamic events |
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