Memory Evolutionary Algorithm Based on Adaptive Dimension Selection
Dan Song · Jisuanji gongcheng · 2011
This paper proposes a Memory Evolutionary Algorithm Based on Adaptive Selecting Dimension(MEABASD).It sets a three-dimensional array to save useful evolutionary information in order to guide the evolution of the follow-up,which can enhance the local search ability.In mutation process,combining with memory information,it adaptively selects the dimension to mutation to strengthen the effectiveness of mutation.The best contemporary populations does self-learning operator to improve the precision of the algorithm.Simulation results on standard test functions show that the algorithm is suitable for the high-dimension optimization problem,and it has the characteristics of rapid convergence,powerful global search capability and high stability.