| 离散微粒群优化算法的研究进展 |
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| 引用本文： | 潘全科,王凌,高亮. 离散微粒群优化算法的研究进展[J]. 控制与决策, 2009, 24(10): 1441-1449 |
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| 作者姓名： | 潘全科 王凌 高亮 |
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| 作者单位： | 聊城大学计算机学院,山东,聊城,252059;清华大学,自动化系,北京,100084;华中科技大学工业及制造系统工程系,武汉,430074 |
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| 基金项目： | 国家自然科学基金项目(60874075,70871065,60774082,60834004);;国家863计划项目(2007AA04Z155);;数字制造装备与技术国家重点实验室(华中科技大学)开放课题 |
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| 摘 要： | 首先，介绍了近年来出现的５种较为典型的离散ＰＳＯ，并分析了它们与基本ＰＳＯ 之间的联系和区别；然后，归纳了提高离散ＰＳＯ 优化性能的若干途径，并总结了离散ＰＳＯ 的应用现状；最后，探讨了离散ＰＳＯ 有待进一步研究的若干方向和内容．
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| 关 键 词： | 微粒群优化 离散微粒群优化 进化计算 群智能 组合优化 |
| 收稿时间： | 2008-09-18 |
| 修稿时间： | 2009-01-28 |
The-state-of-art of discrete particle swarm optimization algorithms |
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| PAN Quan-ke,WANG Ling,GAO Liang. The-state-of-art of discrete particle swarm optimization algorithms[J]. Control and Decision, 2009, 24(10): 1441-1449 |
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| Authors: | PAN Quan-ke WANG Ling GAO Liang |
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| Affiliation: | 1.School of Computer Science;Liaocheng University;Liaocheng 252059;China;2.Department of Automation;Tsinghua University;Beijing 100084;3.Department of Industrial and Manufacturing System Engineering;Huazhong University of Science and Technology;Wuhan 430074;China |
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| Abstract: | Five kinds of representative discrete particle swarm optimization(PSO)algorithms presented in recent years are introduced in this paper.And the relation and distinction between the discrete PSO and the basic PSO are analyzed.Then several methods to improve the discrete PSO algorithms are comprehensively analyzed and concluded.Also,the state of art in the application of the discrete PSO algorithm is investigated in detail.Finally,further research issues and some suggestion about the discrete PSO algorithm in... |
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| Keywords: | Particle swarm optimization Discrete PSO Evolutionary computation Swarm intelligence Combinatorial optimization |
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