López Jaimes, Antonio; Coello Coello, Carlos A.; Aguirre, Hernán; Tanaka, Kiyoshi Objective space partitioning using conflict information for solving many-objective problems. (English) Zbl 1341.90125 Inf. Sci. 268, 305-327 (2014). Summary: We present an algorithm that partitions the objective space based on an analysis of the conflict information obtained from the current Pareto front approximation. By partitioning the objectives in terms of the conflict among them, we aim to separate the multiobjective optimization into several subproblems in such a way that each of them contains the information to preserve as much as possible the structure of the original problem. We implement this framework by performing ranking and parent selection independently in each subspace. Our experimental results show that the proposed conflict-based partition strategy outperforms a similar algorithm in a test problem with independent groups of objectives. In addition, the new strategy achieves a better convergence and distribution than that produced by a strategy that creates subspaces at random. In problems in which the degree of conflict among the objectives is significantly different, the conflict-based strategy presents a better performance. Cited in 2 Documents MSC: 90C29 Multi-objective and goal programming Keywords:multiobjective optimization; many-objective optimization; space partitioning; objective conflict; objective correlation Software:MSOPS-II; SPEA2 PDFBibTeX XMLCite \textit{A. López Jaimes} et al., Inf. Sci. 268, 305--327 (2014; Zbl 1341.90125) Full Text: DOI References: [1] Agrell, P. J., On redundancy in multi criteria decision making, Eur. J. Oper. Res., 98, 571-586 (1997) · Zbl 0917.90207 [2] Aguirre, H. E.; Tanaka, K., Many-objective optimization by space partitioning and adaptive e-ranking on MNK-landscapes, (Ehrgott, M.; Fonseca, C. M.; Gandibleux, X.; Hao, J. K.; Sevaux, M., EMO 2009. 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