计算机应用研究2013，Vol.30Issue(4)：981-985,5.DOI:10.3969/j.issn.1001-3695.2013.04.005
连续空间二元粒子群算法理论研究综述
Research of continuing binary particle swarm optimization
摘要
Abstract
Separating the searching space from the solution space, the binary particle swarm optimization has good performance in the discrete combinational optimization problems and continuous optimization problems. However, the drawbacks that easy to fall into the local optimization and the discrete mechanism still exist. Starting with the improvement of the discrete mechanism and the fusion of the algorithm as well as the algorithm description tool, this paper discussed a series of schemes on improving the binary particle swarm optimization, and also provided the new applications. Finally, it presented some remarks on the futher research.关键词
连续空间二元粒子群算法(CBPSO)/离散化机理/算法融合/协同控制/细胞自动机(CA)Key words
continuing binary particle swarm optimization (CBPSO)/ discrete mechanism/ fusion algorithm/ coordinate control/ cellular automata(CA)分类
信息技术与安全科学引用本文复制引用
程美英,钱乾,熊伟清,周鸣争..连续空间二元粒子群算法理论研究综述[J].计算机应用研究,2013,30(4):981-985,5.基金项目
安徽省教育厅自然科学基金重点资助项目(KJ2007A046,KJ2011Z131) （KJ2007A046,KJ2011Z131）
安徽省教育厅自然科学研究项目(KJ2013Z089) （KJ2013Z089）
安徽商贸职业技术学院院级科研资助项目(KY20100624,2011KYZ01) （KY20100624,2011KYZ01）
