Solving dynamic multi-objective optimization problem of immersed tunnel elements via multi-source evolutionary information clustering method

Qinqin Fan, Wentao Huang, Moduo Yu, Qirong Tang, Qingchao Jiang

Abstract: Highlights•Multi-source population information is considered in the proposed algorithm to adapt to dynamic optimization environments.•A parallel computing method is used to save the computational time.•The results demonstrate that the MPC-RM-MEDA outperforms competitors on both benchmark test functions and an actual DMOP.