关键词: 多目标进化算法, 协同进化, 自适应, 收敛性, 分布性

Abstract: In order to improve the global convergence of co-evolutionary multi-objective evolutionary algorithm, an adaptive method to call co-evolution operator is proposed. The basic idea of method is that co-evolution operators are dynamically called according to the change rate of objective function. When the evolution is normal, cooperation operator and merging operator are called, and otherwise division operator is called. The convergence and distribution of improved algorithm are studied by means of numerical experiments, and results show that the new algorithm not only has good distribution, but also global convergence has been significantly improved compared with the conventional co-evolutionary multi-objective evolutionary algorithm.

Key words: multi-objective evolutionary algorithm, co-evolution, adaptive, convergence, distribution