基于混合策略的引力搜索算法

为了提高引力搜索算法(gravitational search algorithm, GSA)在处理单目标优化问题上的综合能力,提出了一种基于混合改进策略的GSA。依照种群个体自身的进化情况,提出个体进化率的进化策略,以提高算法的收敛速度；采取方向性的变异策略,较好地平衡了全局搜索能力和局部开采能力,最大限度地降低了种群陷入局部最优的可能。基于标准测试函数的仿真实验表明,基于混合策略的GSA算法可有效避免早熟收敛,在收敛精度和收敛速度上与标准的GSA算法以及相应的改进算法相比有显著提高。

Gravitational search algorithm with mixed strategy

In order to improve the performance of the gravitational search algorithm (GSA) in solving single objective optimization problems, a new GSA with mixed improved strategy is proposed. According to the evolution situation, the individual evolution rate strategy is proposed which is applied to enhance the rate of convergence. And a kind of variation strategy is adopted to balance the ability of global searching and local exploiting which avoid the possibility that the population fall into local optimum. Simulation experimental results on benchmark functions show that the GSA with mixed strategy has a good performance in avoiding premature convergence. Compared with GSA and other improved GSA, the new algorithm has a good performance not only in convergence rate but also in convergence precision.