Deriving filtering algorithms from dedicated algorithms: zoom on the Bin Packing problem

Abstract : Solving NP-complete problems can be tough because of the combinatorics. Constraint Programming and Approximation algorithms can be used to solve these problems. In this paper, we explore how to automatically derive filtering algorithms from a dedicated algorithm solving the Bin Packing problem. To this end, we automatically derive a filtering algorithm from the Best-Fit algorithm. We empirically show that our filtering algorithm BF-Prop is experimentally strictly more efficient in terms of filtering than Shaw’s state-of-the-art global constraint.
Type de document :
Communication dans un congrès
CP 2018 - The 24th International Conference on Principles and Practice of Constraints Programming, Aug 2018, Lille, France. 9 p., 2018, Doctoral Program Proceedings. 〈http://cp2018.a4cp.org/dp-proceedings.pdf#page=7〉
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https://hal-mines-albi.archives-ouvertes.fr/hal-01923740
Contributeur : Imt Mines Albi Ecole Nationale Supérieure Des Mines d'Albi-Carmaux <>
Soumis le : jeudi 15 novembre 2018 - 14:01:59
Dernière modification le : jeudi 6 décembre 2018 - 01:23:40

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  • HAL Id : hal-01923740, version 1

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Arthur Godet, Xavier Lorca, Gilles Simonin. Deriving filtering algorithms from dedicated algorithms: zoom on the Bin Packing problem. CP 2018 - The 24th International Conference on Principles and Practice of Constraints Programming, Aug 2018, Lille, France. 9 p., 2018, Doctoral Program Proceedings. 〈http://cp2018.a4cp.org/dp-proceedings.pdf#page=7〉. 〈hal-01923740〉

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