Abstract：On the shortcoming of easily plunged into local optimum of krill herd algorithm(KH)in solving high dimensional complex optimization problem,an improved krill herd algorithm based on natural selection and random disturbance(ANRKH)is proposed.This algorithm firstly applies nonlinear decreasing strategy based on time of induced weight and foraging weight into KH,induced movement and foraging activity of krill herd is improved highly.And then random disturbance factor is added into the process of generating the new generation of krill herd population.And the evolution of the survival of the fittest in natural selection mechanism enhances the quality of the individuals in the krill herd population.Those steps can effectively balance the exploration and development ability of KH.Finally through the experiments of 9 Benchmark standard test functions,this proposed algorithm compares with other algorithms.Experimental results demonstrate that this proposed algorithm can effectively avoid premature convergence problem,the abilities of global search and local exploration have a significant advantage.
刘沛，高岳林，郭伟. 基于自然选择和随机扰动的改进磷虾群算法[J]. 小型微型计算机系统, 2017, 38(8): 1845-1849.
LIU Pei,GAO Yue-lin,GUO Wei. Improved Krill Herd Algorithm Based on Natural Selection and Random Disturbance. Journal of Chinese Computer Systems, 2017, 38(8): 1845-1849.