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| 一种求解Job-Shop调度问题的混合自适应变异粒子群算法 | |
| 引用本文： | 邓慈云,陈焕文,刘泽文,万杰.一种求解Job-Shop调度问题的混合自适应变异粒子群算法[J].计算机工程与科学,2010,32(1):47-49. |
| 作者姓名： | 邓慈云 陈焕文 刘泽文 万杰 |
| 作者单位： | 1. 长沙理工大学计算机与通信工程学院,湖南,长沙,410076 2. 长沙理工大学计算机与通信工程学院,湖南,长沙,410076;湖南信息职业技术学院,湖南,长沙,410200 3. 湖南信息职业技术学院,湖南,长沙,410200 |
| 摘 要： | 本文提出了用于解决车间作业调度问题的混合自适应变异粒子群算法,该算法在运行的过程中根据群体适应度方差以及当前最优解的大小来确定当前最佳粒子的变异概率,利用遗传算法思想对粒子进行选择、交叉操作,并将模拟退火算法的优点融入到AMPSO算法中。仿真结果表明,混合AMPSO算法能够有效地、高质量地解决作业车间调度问题。 |
| 关 键 词： | 粒子群优化 遗传算法 车间作业调度 |
| 收稿时间： | 2008-10-30 |
| 修稿时间： | 2009-01-23 |
A Hybrid Adaptive Mutation Particle Swarm Optimization Algorithm for Job-Shop Scheduling |
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| DENG Ci-yun,CHEN Huan-wen,LIU Ze-wen,WAN Jie.A Hybrid Adaptive Mutation Particle Swarm Optimization Algorithm for Job-Shop Scheduling[J].Computer Engineering & Science,2010,32(1):47-49. | |
| Authors: | DENG Ci-yun CHEN Huan-wen LIU Ze-wen WAN Jie |
| Affiliation: | 1.School of Computer and Communications/a>;Changsha University of Science and Technology/a>;Changsha 410076/a>;2.Hunan College of Information/a>;Changsha 410200/a>;China |
| Abstract: | A Hybrid Adaptive Mutation Particle Swarm Optimization algorithm is proposed for the Job Shop scheduling problem. In the process of running,the mutation probability for the current best particle is determined by two factors:the variance of the population's fitness and the current optimal solution. Through combining genetic algorithms and simulated annealing algorithms with the Adaptive Mutation PSO algorithm,numerical simulation demonstrates that within the framework of the newly designed hybrid algorithm,t... |
| Keywords: | particle swarm optimization genetic algorithm job-shop scheduling |
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