| 一种求解车间调度的混合算法 |
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| 引用本文： | 张长胜,孙吉贵,杨轻云,郑黎辉.一种求解车间调度的混合算法[J].自动化学报,2009,35(3):332-336. |
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| 作者姓名： | 张长胜 孙吉贵 杨轻云 郑黎辉 |
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| 作者单位： | 1.吉林大学符号计算与知识工程教育部重点实验室 长春 130012 |
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| 基金项目： | 国家自然科学基金，东北师范大学自然科学青年基金 |
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| 摘 要： | 针对流水车间作业调度问题, 提出了一种基于``alldifferent'约束的混合进化算法(Hybrid particle and genetic algorithm, HPGA), 将粒子群算法、遗传操作及模拟退火策略有效地结合在一起. 为了提高算法的求解质量, 引入了一种随机邻域搜索策略. 最后将此算法在不同规模的实例上进行了测试, 并与其他几种最近提出的具有代表性的算法进行了比较. 结果表明, 无论是在求解质量还是收敛速度方面都优于其他几种算法.
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| 关 键 词： | 车间调度 粒子群算法 变异 |
| 收稿时间： | 2008-1-17 |
| 修稿时间： | 2008-4-11 |
A Hybrid Algorithm for Flowshop Scheduling Problem |
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| ZHANG Chang-Sheng SUN Ji-Gui YANG Qing-Yun ZHENG Li-Hui .Key Laboratory of Symbol Computation , Knowledge Engineer,Ministry of Education,Jilin University,Changchun .Changchun Institute of Optics,Fine Mechanics , Physics,Chinese Academy of Sciences,Changchun.A Hybrid Algorithm for Flowshop Scheduling Problem[J].Acta Automatica Sinica,2009,35(3):332-336. |
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| Authors: | ZHANG Chang-Sheng SUN Ji-Gui YANG Qing-Yun ZHENG Li-Hui Key Laboratory of Symbol Computation Knowledge Engineer Ministry of Education Jilin University Changchun Changchun Institute of Optics Fine Mechanics Physics Chinese Academy of Sciences Changchun |
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| Affiliation: | 1.Key Laboratory of Symbol Computation and Knowledge Engineer, Ministry of Education, Jilin University, Changchun 130012;2.Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130012 |
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| Abstract: | A hybrid particle and genetic algorithm (HPGA) based on the ``alldifferent' constraint is proposed to solve the flowshop scheduling problem, which combines the particle swarm optimization algorithm, genetic operators, and annealing strategy together. To improve the algorithm's performance further, a neighborhood based local search strategy is proposed and introduced into HPGA. Finally, the HPGA is tested on different scale benchmarks and compared with the recently proposed efficient algorithms. The result shows that both the solution quality and the stability of the HPGA precede the other two algorithms. |
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| Keywords: | Flowshop scheduling partical swarm optimization (PSO) mutation |
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