Neutral Neighbors in Bi-objective Optimization: Distribution of the Most Promising for Permutation Problems

Abstract : In multi-objective optimization approaches, considering neutral neighbors during the exploration has already proved its efficiency. The aim of this article is to go further in the comprehensibility of neutrality. In particular, we propose a definition of most promising neutral neighbors and study in details their distribution within neutral neighbors. As the correlation between objectives has an important impact on neighbors distribution, it will be studied. Three permutation problems are used as case studies and conclusions about neutrality encountered in these problems are provided.
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Communication dans un congrès
Evolutionary Multi-Criterion Optimization, 2017, Munster, Germany. 2017, Evolutionary Multi-Criterion Optimization - 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings. 〈http://www.emo2017.org/〉. 〈10.1007/978-3-319-54157-0_24〉
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https://hal.archives-ouvertes.fr/hal-01566859
Contributeur : Marie-Eléonore Kessaci <>
Soumis le : vendredi 21 juillet 2017 - 13:01:06
Dernière modification le : vendredi 19 janvier 2018 - 13:14:18

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Marie-Eléonore Kessaci, Clarisse Dhaenens, Jérémie Humeau. Neutral Neighbors in Bi-objective Optimization: Distribution of the Most Promising for Permutation Problems. Evolutionary Multi-Criterion Optimization, 2017, Munster, Germany. 2017, Evolutionary Multi-Criterion Optimization - 9th International Conference, EMO 2017, Münster, Germany, March 19-22, 2017, Proceedings. 〈http://www.emo2017.org/〉. 〈10.1007/978-3-319-54157-0_24〉. 〈hal-01566859〉

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