| 粒子群优化与差分进化混合算法的综述与分类 |
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| 引用本文： | 辛斌,陈杰.粒子群优化与差分进化混合算法的综述与分类[J].系统科学与数学,2011,31(9):1130-1150. |
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| 作者姓名： | 辛斌 陈杰 |
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| 作者单位： | 1. “复杂系统智能控制与决策”教育部重点实验室;北京理工大学自动化学院, 北京100081;曼彻斯特大学商学院认知与决策科学研究中心, 曼彻斯特M15 6PB
2. “复杂系统智能控制与决策”教育部重点实验室;北京理工大学自动化学院, 北京100081 |
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| 基金项目： | 国家杰出青年科学基金(60925011) |
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| 摘 要： | 优化算法的性能改进长期以来一直是算法研究者们追求的一个重要目标,对不同算法进行混合以期利用算法的互补优势来获得性能更优异的算法代表了一类典型的设计思想.针对两类基于群体演化的优化算法——粒子群优化(PSO)与差分进化(DE)算法,对基于二者的各种混合算法(DEPSO)进行了系统而全面的综述,并在此基础上提出了一种混合策...
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| 关 键 词： | 优化 混合策略 粒子群优化 差分进化 探索与开发 |
A SURVEY AND TAXONOMY ON HYBRID ALGORITHMS BASED ON PARTICLE SWARM OPTIMIZATION AND DIFFERENTIAL EVOLUTION |
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| XIN Bin
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CHEN Jie.A SURVEY AND TAXONOMY ON HYBRID ALGORITHMS BASED ON PARTICLE SWARM OPTIMIZATION AND DIFFERENTIAL EVOLUTION[J].Journal of Systems Science and Mathematical Sciences,2011,31(9):1130-1150. |
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| Authors: | XIN Bin CHEN Jie |
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| Institution: | XIN Bin (Key Laboratory of Complex System Intelligent.Control and Decision,Ministry of Education,School of Automation,Beijing Institute of Technology,Beijing 100081,Decision and Cognitive Sciences Research Centre,Manchester Business School,The University of Manchester,Manchester M15 6PB) CHEN Jie (Key Laboratory of Complex System Intelligent Control and Decision,Beijing 100081) |
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| Abstract: | Improving the performance of optimization algorithms has long been an important pursuit of researchers.It is a typical design idea and paradigm to combine different optimizers for a synergy of their complementary advantages.Regarding two kinds of population-based evolutionary algorithms,the particle swarm optimizer(PSO) and the differential evolution (DE),we present a systematic and comprehensive survey on their hybrids(DEPSOs) in the literature and propose a taxonomy of hybridization strategies.Based on th... |
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| Keywords: | Optimization hybridization strategy particle swarm optimization differential evolution exploration and exploitation |
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