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

Arthur Godet; Xavier Lorca; Gilles Simonin

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

Arthur Godet ^{1, 2} Xavier Lorca ³ Gilles Simonin ^{1, 2}

1 IMT Atlantique - DAPI - Département Automatique, Productique et Informatique

2 TASC - Théorie, Algorithmes et Systèmes en Contraintes

LS2N - Laboratoire des Sciences du Numérique de Nantes

3 CGI - Centre Génie Industriel

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.

Keywords : constraint programming approximation algorithms bin packing problem filtering algorithms

Document type :

Conference papers

Domain :

Engineering Sciences [physics]

Complete list of metadatas

https://hal-mines-albi.archives-ouvertes.fr/hal-01923740
Contributor : Imt Mines Albi Ecole Nationale Supérieure Des Mines d'Albi-Carmaux <>
Submitted on : Thursday, November 15, 2018 - 2:01:59 PM
Last modification on : Thursday, March 12, 2020 - 3:20:03 PM

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

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

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