The unbiased black-box complexity of partition is polynomial

Benjamin Doerr 1 Carola Doerr 2, 3 Timo Kötzing 4
1 LIX, Ecole Polytechnique
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
3 RO - Recherche Opérationnelle
LIP6 - Laboratoire d'Informatique de Paris 6
Abstract : Unbiased black-box complexity was introduced as a refined complexity model for randomized search heuristics (Lehre and Witt (2012) [24]). For several problems, this notion avoids the unrealistically low complexity results given by the classical model of Droste et al. (2006) [10]. We show that for some problems the unbiased black-box complexity remains artificially small. More precisely, for two different formulations of an NP-hard subclass of the well-known Partition problem, we give mutation-only unbiased black-box algorithms having complexity O(nlog⁡n). This indicates that also the unary unbiased black-box complexity does not give a complete picture of the true difficulty of this problem for randomized search heuristics.
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https://hal.sorbonne-universite.fr/hal-01086507
Contributeur : Carola Doerr <>
Soumis le : lundi 24 novembre 2014 - 13:23:46
Dernière modification le : jeudi 10 mai 2018 - 02:06:18

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Benjamin Doerr, Carola Doerr, Timo Kötzing. The unbiased black-box complexity of partition is polynomial. Artificial Intelligence, Elsevier, 2014, 216, pp.12. 〈http://www.sciencedirect.com/science/article/pii/S000437021400099X〉. 〈10.1016/j.artint.2014.07.009〉. 〈hal-01086507〉

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