A Multi-objective Cuckoo search Algorithm Based on Decomposition
Liang Chen, Wenyan Gan, Hongwei Li, Xin Xu, Lin Cao, Yufang Feng · 2019
The simplicity and success of cuckoo search (CS) algorithm has inspired researchers to apply these techniques to the multi-objective optimization field. The paper studies the application of CS for solving multi-objective optimization problems (MOPs) based on decomposition methods. A new decomposition-based multi-objective CS algorithm is proposed, called MOCS/D. The proposed algorithm integrates the unique Lévy flights technique of CS and improved polynomial mutation into multi-objective evolutionary algorithm based on Decomposition (MOEA/D). Our proposed approach is compared with MOEA/D-SBX and MOEA/D-DE on the test instances. The experimental results show that it outperforms the compared algorithms on most of the selected test instances. It demonstrates that the proposed approach is a competitive candidate for multi-objective optimization problems.