| 应用改进微粒群算法求解Job-shop调度问题 |
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| 引用本文： | 柳毅,叶春明,沈运红. 应用改进微粒群算法求解Job-shop调度问题[J]. 系统工程与电子技术, 2006, 28(4): 602-606 |
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| 作者姓名： | 柳毅 叶春明 沈运红 |
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| 作者单位： | 上海理工大学管理工程学院,上海,200093 |
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| 基金项目： | 上海市教委发展基金项目(02GK13) |
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| 摘 要： | 针对微粒群算法在求解实际问题过程中会出现早熟的现象,提出一种改进的微粒群算法。该算法利用记忆库来动态调整惯性权重值,增快了算法的收敛速度。同时结合进化、灾变机制避免了算法陷入局部极值的问题。在列出改进算法的具体步骤基础上,通过实际的车间调度仿真实例证明了算法的有效性,可以得到比启发式、遗传算法更佳的调度效果。
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| 关 键 词： | Job-shop调度问题 微粒群算法 进化算法 |
| 文章编号： | 1001-506X(2006)04-0602-05 |
| 修稿时间： | 2005-04-20 |
Solving the Job-shop scheduling problem based on improved particle swarm algorithm |
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| LIU Yi,YE Chun-ming,SHEN Yun-hong. Solving the Job-shop scheduling problem based on improved particle swarm algorithm[J]. System Engineering and Electronics, 2006, 28(4): 602-606 |
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| Authors: | LIU Yi YE Chun-ming SHEN Yun-hong |
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| Abstract: | Improved particle swarm optimization algorithm is presented for overcoming the slow and premature convergence of the classic particle swarm algorithm. Some methods of evolution mechanism,constructing feasible solution space and adaptive inertia weight are presented to enhance capability of algorithm searching the best global solution.Simulation results verify the proposed algorithm is effective, and it is superior to GA and heuristic algorithm. |
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| Keywords: | Job-shop scheduling problem particle swarm optimization evolutionary algorithm |
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