摘要
受生态系统中迁移机制的激发,提出了一种基于群体迁移的优化算法.该算法是根据生态学中群体分布的迁移模型而提出的一种新的优化算法.借鉴其他智能算法思想,用栖息地来表示优化问题的解集,通过生物群体的迁入与迁出实现解集之间特征信息的共享,从而完成进化过程.该文讨论了基于群体迁移的优化算法基本原理和实现步骤,同时进行一些基准函数的性能测试.通过分析表明提出的新算法是有效的,是一种具有潜在优越性的优化算法.
Motivated by migration mechanisms of ecosystems, a species migration-based optimization algorithm （SMOA） is proposed. SMOA is a new optimization method bawd on the migration model of organism distribution in biological systems. Inspired by the development of other intelligence algorithms, problem solutions are represented as habitats; and the sharing of features between solutions is representext as species immigration and emigration in SMOA. This paper discusses the principle and steps of implementation in SMOA, and explores performance through benchmark functions. The performance study shows that the proposed algorithm is effective and is a promising candidate for optimiza-tion.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2010年第3期329-334,343,共7页
Control Theory & Applications
关键词
优化算法
群体迁移
函数优化
计算智能
optimization algorithm
species migration
function optimization
computer intelligence
