关键词: 多目标优化, 布估计算法, 差分进化算法, 自适应, 函数变化率

Abstract: An adaptive hybrid multi-objective estimation of distribution evolutionary algorithm based on the change rate of objective function is put forward for overcoming the defect in global convergence of multi-objective estimation of distribution algorithm. The basic idea of new method is that differential evolution algorithm is introduced into multi-objective estimation of distribution algorithm. When the change rate of function is large, new population is generated with estimation of distribution algorithm, and otherwise differential evolution algorithm is used to generate new population. Theoretical analysis and numerical results show that the hybrid algorithm has better global convergence, and the distribution and uniformity of solutions is improved to a certain extent compared with algorithm without considering the change rate of objective function.

Key words: multi-objective optimization, estimation of distribution algorithm, differential evolution algorithm, adaptive, change rate of function