| 一种改进的混沌粒子群优化混合算法 |
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| 引用本文： | 钱晓山.一种改进的混沌粒子群优化混合算法[J].应用科技,2012,39(1):5-8. |
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| 作者姓名： | 钱晓山 |
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| 作者单位： | 宜春学院物理科学与工程技术学院,江西宜春,336000;中南大学信息科学与工程学院,湖南长沙,410083 |
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| 基金项目： | 基金项目：国家自然科学基金资助项目（60874069）;国家863计划资助项目（2009AA042124,2009AA042137）. |
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| 摘 要： | 提出了一种改进的混沌粒子群优化混合算法.该算法利用信息交换机制将两组种群分别用差分进化算法和粒子群算法进行协同进化,并且将混沌变异操作引入其中,加强算法的局部搜索能力.通过对3个标准函数进行测试,仿真结果表明该算法与差分进化粒子群优化（DEPSO）算法相比,全局搜索能力和抗早熟收敛性能大大提高.
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| 关 键 词： | 混合算法 差分进化 粒子群优化 协同进化 混沌变异 早熟收敛 |
A hybrid algorithm of the improved chaotic particle swarm optimization |
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| QIAN Xiaoshan.A hybrid algorithm of the improved chaotic particle swarm optimization[J].Applied Science and Technology,2012,39(1):5-8. |
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| Authors: | QIAN Xiaoshan |
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| Institution: | QIAN Xiaoshan(. College of Physical Science and Engineering Technology, Yichun University, Yichun 336000, China 2. School of Information Science＆Engineering, Central South University, Changsha 410083, China |
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| Abstract: | A hybrid algorithm of the improved chaotic particle swarm optimization is proposed. Based on the information exchange mechanism, the algorithm uses differential evolution algorithm and particle swarm algorithm to make co-evolution for two groups of populations, and the chaos mutation is introduced into the algorithm to enhance the efficiency of local search capabilities. Using three standard functions to test it, simulation results show that, compared with the differential evolution and particle swarm optimization （DEPSO） algorithm, global search ability and resistance to premature convergence are increased greatly. |
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| Keywords: | hybrid algorithm differential evolution optimization particle swarm co-evolution chaotic variation premature convergence |
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