南通大学学报：自然科学版2012，Vol.11Issue(2)：1-8,8.
一种新的群搜索优化实现算法
A Novel Realization Algorithm of Group Search Optimizer
摘要
Abstract
A novel realization algorithm of group search optimizer （NRGSO） is proposed, aiming at overcoming the deficiency of GSO. And it is easier to be applied in practical problems. Five test functions of 300 dimensions and seven test functions of 30 dimensions are used to conduct the numerical experiments and the results of the novel algo-rithm are compared with those of GSO, particle swarm optimization （PSO）, genetic algorithm （GA）, evolutionary programming （EP） and evolutionary strategy （ES）. The algorithm proposed in this paper is better than GSO and its performance in solving the problems of high dimensions and multimodal functions is better than PSO, GA, EP and ES. NRGSO improves the original algorithm. It enhances its search ability and achieves better results. This novel algorithm performs excellently in functions of high dimensions, can effectively avoid being trapped in the local minima and is applicable in practical optimizer.关键词
群搜索优化/函数优化/多模态函数/高维函数/算法Key words
group search optimizer/function optimization/multimodal functions/functions of high dimensions/algorithm分类
计算机与自动化引用本文复制引用
罗磊,谢静,周晖,梁天,冯绍杰,庆栋良..一种新的群搜索优化实现算法[J].南通大学学报：自然科学版,2012,11(2):1-8,8.基金项目
国家自然科学基金资助项目 （）
江苏省2011年度普通高校研究生科研创新计划项目 （）
江苏省高校社会科学研究项目 （）
南通大学研究生科技创新计划项目 （）
