| 改进微粒群优化求解置换流水车间调度问题 |
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| 引用本文： | 刘延风,刘三阳. 改进微粒群优化求解置换流水车间调度问题[J]. 计算机集成制造系统, 2009, 15(10) |
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| 作者姓名： | 刘延风 刘三阳 |
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| 作者单位： | 西安电子科技大学,应用数学系,陕西,西安,710071;西安电子科技大学,应用数学系,陕西,西安,710071 |
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| 基金项目： | 国家自然科学基金资助项目(60703118)~~ |
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| 摘 要： | 针对置换流水车间调度问题,提出了一种改进微粒群优化的求解算法。首先,由基于启发式信息的贪婪随机自适应算法得到工件加工顺序,个体最优的初始值不再是随机生成的初始值,而是由该工件加工顺序转化而成;然后,对个体最优解进行了交换型局部搜索;最后,通过对Car系列和Rec系列基准的测试,表明了该算法的有效性。
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| 关 键 词： | 置换流水车间 调度 微粒群优化 贪婪随机自适应算法 局部搜索 |
Improved particle swarm optimization for permutation flow shop scheduling problems |
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| LIU Yan-feng,LIU San-yang. Improved particle swarm optimization for permutation flow shop scheduling problems[J]. Computer Integrated Manufacturing Systems, 2009, 15(10) |
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| Authors: | LIU Yan-feng LIU San-yang |
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| Affiliation: | Department of Applied Mathematics;Xidian University;Xi'an 710071;China |
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| Abstract: | To solve permutation flow shop scheduling problems,an Improved Particle Swarm Optimization(IPSO) algorithm was proposed.Firstly,each sequence of jobs was generated by greedy randomized adaptive search based on heuristics.The initial best position of each particle was no longer the randomly generated initial position of each particle,it was converted from above sequence of jobs.Then,a swap-based local search was applied for the best position of each particle.Finally,the simulation results based on benchmarks... |
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| Keywords: | permutation flow shop scheduling particle swarm optimization greedy randomized adaptive search local search |
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