多策略自适应共生生物搜索算法

Multi-strategy Adaptive Symbiotic Organisms Search Algorithm

针对共生生物搜索算法搜索速度慢、收敛精度不高且易早熟的缺点,提出了一种多策略自适应改进算法。首先,根据适应度将种群分为3个群体,每个群体采用不同的搜索策略以实现不同功能。其次,提出了一种基于实时信息反馈的的混合搜索策略,使其搜索策略实现自适应调整。最后,对超边界个体进行变异操作,以增加种群多样性。对14个标准测试函数的仿真测试表明改进算法全局优化能力更强,具有更好的搜索速度和收敛精度。

Aimed at the problems that Symbiotic Organisms Search （SOS）algorithm is poor in conver-gence,low in searching precision and ease of premature convergence,a multi-strategy adaptive algorithm is proposed.Firstly,according to the fitness,populations can be divided into three groups,and each group with different strategies can achieve different functions.Secondly,a hybrid search strategy based on adap-tive scaling factor can make its search strategy realization of the adaptive adj ustment.Finally,in order to maintain the population diversity,a mutation is utilized when the individual beyond the boundary.Experi-ments are conducted on the 14 benchmark functions,and the results show that the MSASOS algorithm improves obviously the performance in convergence speed,precision and global optimization.