A Kind of Multi-objective Optimization Algorithm Based on Differential Evolution with Multi-population Mechanism
Yi Zhuang · 2012
In order to avoid the situation of falling into local optimum in solving the multi-objective optimization problem(MOP) with differential evolution algorithm(DE),we designed a bidirectional search mechanism which can improve the ability of local search of the DE.We also designed a multi-population mechanism for DE,which can reduce the risk of local optimum,and make the Pareto fronts more evenly distributed.Experimental results shows that,compared with similar algorithms such as NSGA-II,the proposed method is more efficient,while the precision and distribution of Pareto optimal solution set is better than the former.