期刊
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
卷 16, 期 9, 页码 3696-3703出版社
ELSEVIER
DOI: 10.1016/j.cnsns.2010.12.025
关键词
Big Bang-Big Crunch optimization; Chaos; Metaheuristic optimization; Soft computing; Uniform population
This study proposes methods to improve the convergence of the novel optimization method, Big Bang-Big Crunch (BB-BC). Uniform population method has been used to generate uniformly distributed random points in the Big Bang phase. Chaos has been utilized to rapidly shrink those points to a single representative point via a center of mass in the Big Crunch phase. The proposed algorithm has been named as Uniform Big Bang-Chaotic Big Crunch (UBB-CBC). The performance of the UBB-CBC optimization algorithm demonstrates superiority over the BB-BC optimization for the benchmark functions. (C) 2010 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据