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DOI:
计算机系统应用英文版:2012,21(3):167-170,223
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混合粒子群算法及在可靠性优化中的应用
(浙江万里学院,宁波 315101)
Hybrid Particle Swarm Optimization Algorithm and the Application of Reliability Optimization
(Zhejiang Wanlin University, Ningbo 315101 China)
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Received:June 21, 2011    Revised:September 09, 2011
中文摘要: 针对粒子群算法搜索精度低和早熟收敛的缺陷,通过算法混合,提出了基于混沌与和声搜索算法思想的混合粒子群优化算法。该算法采用Tent 映射,利用混沌特性提高种群的多样性和粒子搜索的遍历性,同时采用和声策略对解空间进行开发,引入了柯西变异,帮助粒子跳出局部陷阱,采用云模型的自适应策略来调整惯性权重。最后将该优化算法应用于可靠性优化设计中,仿真实验表明,改进后的混合粒子群优化算法较基本粒子群算法收敛速度加快,且不易陷入局部极值点。
Abstract:Particle swarm optimization for search precision is low and the premature convergence of the defect, through the mixing algorithm is proposed and the harmony search algorithm based on chaotic thinking hybrid particle swarm optimization algorithm. The algorithm uses the Tent map, the use of chaotic characteristics to improve the population diversity and particle traversal search, while using sound strategy for development of the solution space, the introduction of the Cauchy mutation, to help jump out of local trap particles using cloud model adaptive strategy to adjust the inertia weight. At last, the optimization algorithm is applied to reliability optimization design, simulation experiments show that the improved hybrid particle swarm optimization algorithm is better than elementary particle swarm optimization algorithm to speed up the convergence rate, and easy to fall into local minimum points.
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李小青.混合粒子群算法及在可靠性优化中的应用.计算机系统应用,2012,21(3):167-170,223
LI Xiao-Qing.Hybrid Particle Swarm Optimization Algorithm and the Application of Reliability Optimization.COMPUTER SYSTEMS APPLICATIONS,2012,21(3):167-170,223