| 基于粒子群优化和模拟退火的混合调度算法 |
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| 引用本文： | 潘全科,王文宏,朱剑英.基于粒子群优化和模拟退火的混合调度算法[J].中国机械工程,2006,17(10):1044-1046,1064. |
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| 作者姓名： | 潘全科 王文宏 朱剑英 |
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| 作者单位： | 1. 聊城大学,聊城,252059
2. 南京航空航天大学,南京,210016 |
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| 基金项目： | 中国科学院资助项目;教育部科学技术研究项目 |
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| 摘 要： | 提出了一种离散粒子群调度算法，采用基于工序的编码方式及相应的位置和速度更新方法，使具有连续本质的粒子群算法直接适用于调度问题。针对粒子群算法容易陷入局部最优的缺陷，将其与模拟退火算法结合，得到了粒子群-模拟退火算法、改进的粒子群算法、粒子群-模拟退火交替算法以及粒子群-模拟退火协同算法等4种混合调度算法。仿真结果表明，混合算法均具有较高的求解质量。
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| 关 键 词： | Job Shop调度问题 粒子群优化 模拟退火算法 混合算法 |
| 文章编号： | 1004-132X（2006）10-1044-03 |
| 收稿时间： | 2005-06-30 |
| 修稿时间： | 2005-06-30 |
Effective Hybrid Heuristics Based on Particle Swarm Optimization and Simulated Annealing Algorithm for Job Shop Scheduling |
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| Pan Quanke,Wang Wenhong,Zhu Jianying.Effective Hybrid Heuristics Based on Particle Swarm Optimization and Simulated Annealing Algorithm for Job Shop Scheduling[J].China Mechanical Engineering,2006,17(10):1044-1046,1064. |
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| Authors: | Pan Quanke Wang Wenhong Zhu Jianying |
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| Affiliation: | 1. Liaocheng University, Liaocheng, Shandong, 252059 ;2. Nanjing University of Aeronautics and Astronautics, Nanjing, 210016 |
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| Abstract: | A discrete particle swarm optimization(PSO) algorithm was presented for Job Shop scheduling problem.In the algorithm,an operation-based representation was developed,and a new method was used to update position of particles with operation-based representation.So PSO can be easily applied to all classes of scheduling problems.But pure PSO may produce premature and poor results.Based on the complementary strengths of PSO and simulated annealing(SA) algorithm,four hybrid procedures were put forward by combining the PSO and SA.Numerical simulation demonstrates that within the framework of the newly designed hybrid algorithm,the NP-hard classic Job Shop scheduling problem can be efficiently solved with higher quality. |
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| Keywords: | Job Shop scheduling problem particle swarm optimization simulated annealing algorithm hybrid procedure |
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