改进的基于局部搜索策略的生物地理学优化算法

Improved Biogeography-Based Optimization Algorithm Based on Local Search Strategy

为了提高生物地理学优化(BBO)算法的优化特性,提出一种改进的基于局部搜索策略的生物地理学优化算法(ILSBBO)。改进的算法将差分进化算法的局部搜索策略与BBO算法的迁移策略进行结合,并引入了差分进化算法中的选择操作。在13个基准测试函数上,对改进的算法、基本BBO算法,以及基于BBO的混合差分进化算法(DE/BBO)进行比较,结果表明改进的算法优于所比较的其他两种算法;此外,改进后的算法在收敛速度上也优于基本BBO算法。

Biogeography-Based Optimization algorithm is a new kind of global optimization algorithm, but its searching capability still needs to be improved. In order to improve the optimization characteristics of the algorithm, this paper proposes an improved algorithm of BBO improved biogeography - based optimization algorithm based on local search strategy （ILSBBO）. The improved approach combines the local search strategy of differential evolution with the migration strategy of BBO, then, the selection operation of differential evolution is introduced to it. Among 13 benchmark test functions, the improved algorithm, the original BBO, and hybrid differential evolution with biogeography-based optimization （DE/BBO） are compared, the resuhs show that the proposed approach is better than the other two approaches. In addition, the convergence rate of the improved algorithm is also faster than the original biogeography - based optimization algorithm.