| 求解Job shop调度的协同优化算法 |
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| 引用本文： | 叶伟,叶春明,何建佳.求解Job shop调度的协同优化算法[J].机械设计与制造,2009(7). |
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| 作者姓名： | 叶伟 叶春明 何建佳 |
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| 作者单位： | 上海理工大学管理学院,上海,200093 |
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| 基金项目： | 上海市重点学科(第二期)项目(T0502) |
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| 摘 要： | 针对量子粒子群算法、遗传算法在求解车间调度存在的局部收敛的问题,提出用量子粒子群算法与遗传算法相结合的协同优化方法求解该问题。该算法采用量子粒子群算法与遗传算法的并行搜索结构,通过迁移算子把各个种群联系起来。仿真结果表明,该算法收敛速度快,且具有较高的求解质量。
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| 关 键 词： | 量子粒子群 遗传算法 jobshop调度 协同优化 |
Solve job-shop scheduling problem based on cooperative optimization |
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| YE Wei,YE Chun-ming,HE Jian-jia.Solve job-shop scheduling problem based on cooperative optimization[J].Machinery Design & Manufacture,2009(7). |
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| Authors: | YE Wei YE Chun-ming HE Jian-jia |
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| Affiliation: | Management School of University of Shanghai for Science and Technology;Shanghai 200093;China |
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| Abstract: | Coping with such disadvantages of particle swam optimization algorithm and GA as being easy to run into local optima,the method that quantum-behaved particle swam optimization hybridize GA is proposed to be applied to job-shop scheduling problem,The algorithm applied the parallel hybrid architecture of collaborative quantum particle swarm and GA,in which a kind migration operator was designed to associate all population.,and the result shows that this algorithm has better answers and more rapid convergence. |
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| Keywords: | Quantum particle swam optimization GA Job-shop scheduling problem Cooperative optimization |
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