关键词: 多目标优化, 离散差分进化, Pareto最优, 自适应

Abstract: An adaptive Multi-objective Discrete Differential Evolution（MDDE） is proposed.By introducing differential evolution to multi-objective optimization，MDDE adopts a new adaptive discrete differential evolution strategy to enhance the ability of global exploration so as to achieve better Pareto approximate solutions.Moreover，for keeping good diversity，MDDE integrates fast Pareto sorting strategy and truncating operation based on crowding density and rank.The experimental results show that the proposed approach is able to effectively solve the multi-objective problems with discrete or continuous solution spaces and has better performance on convergence，diversity and stability.

Key words: multi-objective optimization, discrete differential evolution, Pareto optimal, adaptation