【摘要】 利用基于分解的多目标进化算法框架(MOEA/D),将混合策略的进化算法用于求解分解后的若干单目标优化子问题,提出了一种带局部搜索的基于分解的多目标混合策略进化算法(LMS-MOEA/D)。算法利用均匀设计产生子问题的聚合权重向量,混合交叉策略能够充分利用不同交叉算子的优势;同时算法针对演化过程收敛的特点,结合局部搜索策略,获得逼近Pareto前沿的最优解集。最后通过实验验证算法在多样性和收敛性方面的有效性。更多还原

【Abstract】 A novel algorithm,called multi-objective mixed strategy evolutionary algorithm with local search(LMSMOEA/D),was presented based on the frame of MOEA/D(multi-objective evolutionary algorithm based on decomposition),to solve a set of scalar optimization sub-problems.The uniform design method was applied to generate the aggregation coefficient vectors.The mixed strategy can make full use of the advantage of each crossover operator,and the algorithm combines local search strategy to approximate the Pareto-optimal set.Experimental results indicate that the proposed algorithm has the efficiency and effectiveness in terms of diversity and convergence.更多还原