A Modified MOEAD with an Adaptive Weight Adjustment Strategy
Siwen Xu, Hanning Chen, Xiaodan Liang, Maowei He · 2019
Multiobjective evolutionary algorithm based on decomposition (MOEA/D) is widely used to dispose multiobjective optimization problems (MOPs). The performance of MOEA/D is not ideal when deals with MOPs which are with degenerated curve. Aiming to this weakness, an adaptive weight adjustment strategy named BPO is proposed in this paper. In order to solve this problem, BPO strategy is based on the number of reference points referencing the archive. The results of tests show that MOEA/D with BPO strategy can obtain ideal performance. MOEA/D with BPO strategy can improves the weakness of MOEA/D effectively on MOPs which are with degenerated curve.