Hiroyuki Sato
ABSTRACT
This work proposes a decomposition-based multi-objective evolutionary algorithm utilizing variation angles among objective and weight vectors. The proposed algorithm introduces an angle-based proportional selection and dominance- and angle-based solution comparison criterion. Experimental results using WFG4 and WFG5 problems show that the proposed algorithm achieves better search performance than the conventional MOEA/D and MOEA/D-CRU.
- Q. Zhang, H. Li, "MOEA/D: A Multi-objective Evolutionary Algorithm Based on Decomposition," IEEE Trans. on EC, Vol. 11, No. 6, pp. 712--731, 2007. Google Scholar
Digital Library
- H. Sato, "Chain-Reaction Solution Update in MOEA/D and Its Effects on Multi and Many-Objective Optimization," Soft Computing, Springer, Vol. 20, Issue 10, pp. 3803--3820, 2016. Google ScholarDigital Library
Index Terms
- An improved MOEA/D utilizing variation angles for multi-objective optimization
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