基于混合迁移行为的自组织迁移算法

Hybrid Migrating Behavior Based Self-organizing Migrating Algorithm

自组织迁移算法(Self-organizing migrating algorithm,SOMA)是一种新型的进化算法。在对基本的自组织迁移算法分析的基础上提出了基于混合迁移行为的自组织迁移算法(Hybrid migrating behavior based self-organizing migrating algorithm,HBSOMA)。该算法通过在个体迁移过程中引入了多种迁移方式,形成混合迁移行为,使得个体的行为变得多样化,增加了种群多样性,加速了群体在多峰复杂空间中的寻优进程。仿真结果显示,该算法优于原自组织迁移算法。

Self-organizing migrating algorithm （SOMA） is a new evolutionary algorithm. This paper proposed a hybrid migrating behavior based self-organizing migrating algorithm（HBSOMA） based on the analysis of the basic SOMA, which employs the multiple migrating modes in the individual migration procedure. It increases the diversity of the pop- ulation and speeds up the population-based search process in the multi-modal complex space. Simulation results reveal that the proposed algorithm is better than the original self-organizing migrating algorithm.