Open access
Sep 2026
A hierarchical reinforcement learning based subtask-coordinated scheduling method for constrained multi-objective evolutionary algorithm
Experimental results demonstrate that the proposed method consistently outperforms nine state-of-the-art constrained multi-objective evolutionary algorithms (CMOEAs) in terms of convergence, feasibility, and diversity, thereby confirming its effectiveness and strong general applicability.
Lu-Peng Hao, Yahui Shan, Guang-Yin Jin et al.
· Journal of King Saud Univers... · 0 citations