关键词: 多目标优化 差分演化 种群多样性Pareto最优

Abstract:

Differential evolution is a simple and effective evolutionary algorithm for global optimization. Through extending differential evolution to solve mul  ti-objective optimization problems, a multi-objective differential evolution algorithm with maintaining diversity is presented in this paper. In order t o maintain diversity to improve the search performance, the algorithm employs an orthogonal design method to generate initial population,and modifies di fferential evolution operators. The primary experimental results show that the algorithm is effective for solving multi-objective optimization problems.

Key words: multi-objective optimization, differential evolution, population diversity;Pareto optimal