%0 Journal Article
%T Hybrid optimization method through complete Logistic chaoticparticle swarm optimization and genetic algorithm<br>一种采用完全Logistic混沌的PSO-GA优化方法
%A HUANG Wei-yong
%A <br>黄为勇
%J 计算机应用研究
%D 2012
%I 
%X In order to improve the optimization performance of particle swarm optimization, this paper proposed a new algorithm called complete Logistic chaotic particle swarm optimization combined with genetic algorithm. Logistic chaos search, which had the property of pseudo-randomness and ergodicity, was applied to the initialization of position and velocity of initial swarm, the optimization of inertia weight, the generation of random constant and the generation of the local optimum neighborhood point. After the particle velocity and position were updated, it embedded genetic algorithm in the complete Logistic chao-tic particle swarm optimization, to perform the operation of selection and crossover. Experimental results with three typical Benchmark functions show that the proposed algorithm is effective, and has better search property and convergence speed.
%K chaotic optimization
%K Logistic chaos
%K particle swarm optimization
%K genetic algorithm<br>混沌优化
%K Logistic混沌
%K 粒子群优化
%K 遗传算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=9B3C227A81E2A28C759C226609DDAB73&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=9CF7A0430CBB2DFD&sid=A5D072B7BBE6B11A&eid=C752758852E1E57D&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=15