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Titlebook: Evolutionary Multi-Criterion Optimization; 8th International Co António Gaspar-Cunha,Carlos Henggeler Antunes,Carl Conference proceedings 2

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https://doi.org/10.1007/978-3-319-23895-1indicator-based MOEA (the ., SMS- EMOA) using several test problems (taken from the specialized literature) having from two to ten objective functions. Our preliminary experimental results indicate that our proposed HDE outperforms MOEA/D and is competitive with respect to SMS-EMOA, but at a significantly lower computational cost.
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Klemetti Näkkäläjärvi,Pekka Kauppalaence information one can represent more faithfully the DM’s preferences. Such information about indifference should narrow down the set of compatible value functions much more quickly than standard pairwise comparisons, and a first simple example at least indicates that this intuition seems to be correct.
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Evolutionary Many-Objective Optimization Based on Kuhn-Munkres’ Algorithmindicator-based MOEA (the ., SMS- EMOA) using several test problems (taken from the specialized literature) having from two to ten objective functions. Our preliminary experimental results indicate that our proposed HDE outperforms MOEA/D and is competitive with respect to SMS-EMOA, but at a significantly lower computational cost.
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