A novel multi-objective evolutionary algorithm with dynamic decomposition strategy

Songbai Liu, Qiuzhen Lin, Ka-Chun Wong, Lijia Ma, Carlos A. Coello Coello, Dunwei Gong

Abstract: Highlights•This paper proposes a dynamic decomposition strategy for MOEA/D.•The process of dynamic decomposition in most-crowded region is used to keep the diversity.•A simple convergence indicator is used to ensure the convergence.•The proposed MOEA/D-DDS presents the superior performance over some competitive MOEAs.