摘要
提出一种融合了遗传算法中常用的轮盘赌选择算子,能在早期抑制部分超级粒子对种群控制的混合粒子群算法,并在著名测试函数上实施了比较实验.结果表明,混合算法能以较快的收敛速度获得质量较好的解.
In this paper, a novel Particle Swarm Optimizer combined with the roulette selection operator is proposed, which provides a mechanism to restrain the predominating of super particles in early stage and can effectively avoid the premature problem. Variety experiments are conducted on several test functions taken from the literature. The computational results demonstrate that the modified algorithm is promising to achieve faster convergence and better solutions, especially for multimodal function optimization.
出处
《西南师范大学学报（自然科学版）》
CAS
CSCD
北大核心
2006年第3期93-96,共4页
Journal of Southwest China Normal University(Natural Science Edition)
基金
国家863子专题资助项目(86351191010101)
重庆市信息产业局重点资助项目(200311014)
关键词
粒子群
轮盘赌
多峰函数
早熟收敛
particle swarm optimization
roulette selection
muhimodal function
premature problem
