Evolutionary Programming Algorithm for Solving Numerical Optimization Problems
Yongquan Yu · Jisuanji gongcheng · 2011
Aiming at the problems of Evolutionary Programming(EP) such as premature convergence,slow convergence,this paper proposes an EP algorithm based on probe mutation.It can obtain a few mutational variables by reducing the dimensionality while fixating the others,and makes these individuals mutate which makes the individual always move forward to the direction with high fitness.By applying self-adaptive Gauss standard deviation to recover the search space,the individual has opportunity for jumping out the local optimum solutions.Experimental results show that the improved algorithm converges quickly,has high-quality solutions,and overcomes premature convergence problem.