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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Notes
- 1.
The interval has been chosen as the famous instances proposed by the \(8^{th}\) DIMACS challenge (see http://dimacs.rutgers.edu/Challenges/TSP/).
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Kessaci-Marmion, ME., Dhaenens, C., Humeau, J. (2017). Neutral Neighbors in Bi-objective Optimization: Distribution of the Most Promising for Permutation Problems. In: Trautmann, H., et al. Evolutionary Multi-Criterion Optimization. EMO 2017. Lecture Notes in Computer Science(), vol 10173. Springer, Cham. https://doi.org/10.1007/978-3-319-54157-0_24
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DOI: https://doi.org/10.1007/978-3-319-54157-0_24
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