趋优算子和Levy Flight混合的粒子群优化算法  

Particle Swarm Optimization Algorithm Based on Combining Global-Best Operator and Levy Flight

作　　者：张新明[1,2] 王霞 涂强 康强[1] ZHANG Xin-ming;WANG Xia;TU Qiang;and KANG Qiang(College of Computer and Information Engineering, Henan Normal University Xinxiang Henan 453007;Engineering Technology Research Center for Computing Intelligence ＆ Data Mining of Henan Province Xinxiang Henan 453007)

机构地区：[1]河南师范大学计算机与信息工程学院,河南新乡453007 [2]河南省高校计算智能与数据挖掘工程技术研究中心,河南新乡453007

出　　处：《电子科技大学学报》2018年第3期421-429,共9页Journal of University of Electronic Science and Technology of China

基　　金：河南省重点科技攻关项目(132102110209);河南省基础与前沿技术研究计划(142300410295)

摘　　要：针对Levy Flight粒子群优化算法(LFPSO)普适性不强和搜索效率不高等问题,提出了一种改进的LFPSO算法(ILFPSO),即趋优算子与Levy Flight混合的粒子群优化算法。首先,对Levy Flight进行改进,防止产生无效解,得到改进的Levy Flight;然后,将既有一定全局搜索能力又有较强局部搜索能力的趋优算子与改进的Levy Flight有机融合,以便更好地平衡算法的全局和局部搜索能力;最后,对速度边界动态调整,有利于搜索前期找到全局最优点和搜索后期找到局部最优解。28个benchmark函数优化仿真结果表明,与4种最先进的PSO改进算法LFPSO、ELPSO、SRPSO和RLPSO相比,ILFPSO更具有竞争性的优化性能、更好的普适性和更快的运行速度。In order to enhance the optimization performance of the particle swarm optimization algorithm with Levy Flight（LFPSO）, this paper proposes an improved LFPSO（ILFPSO）, namely PSO based on combining the global-best operator and Levy Flight. First, the Levy Flight operator is accurately improved so that it can prevent the algorithm from generating invalid solutions, and an improved Levy Flight operator is obtained. Then because of the advantage of the global-best operator which has both some global and strong local search ability, this paper combines the global-best operator and improved Levy Flight in order to balance the global and local optimization ability of the algorithm. Finally, the velocity boundary is updated dynamically, which is helpful to find the global optimal solution in the early search stage and local optimal solutions in the later stage. 28 benchmark functions are used to evaluate the feasibility of ILFPSO. The experimental results show that, compared with 4 state-of-the-art PSO variants, such as LFPSO, ELPSO, SRPSO and RLPSO, ILFPSO obtains stronger competitive power, better universality and faster running speed.

关 键 词：趋优算子 智能优化算法 LEVY FLIGHT 粒子群优化算法 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]