L'identification de structures propres à un problème est souvent une étape clef pour la conception d'heuristiques de recherche comme pour la compréhension de la complexité du problème. De nombreuses approches en Recherche Opérationnelle emploient des stratégies de relaxation ou de décomposition dès lors que certaines struc- tures idoines ont été identifiées. L'étape suivante est la conception d'algorithmes de résolution qui puissent intégrer à la volée, pendant la résolution, ce type d'information. Cet article propose d'utiliser un solveur de contraintes à base d'explications pour collecter une information pertinente sur les structures dynamiques et statiques inhérentes au problème.
Explanations for identifying and exploiting structures within combinatorial problems. Identifying structure in a given combinatorial problem is often a key step for designing efficient search heuristics or for understanding the inherent complexity of the problem. Several Operations Research approaches apply decomposition or relaxation strategies upon such a structure identified within a given problem. The next step is to design algorithms that adaptively integrate that kind of information during search. We claim in this paper, inspired by previous work on impact-based search strategies for constraint programming, that using an explanation-based constraint solver may lead to collect invaluable information on the intimate dynamic and static structure of a problem instance.
Mots clés : programmation par contraintes, explications
@article{RO_2006__40_4_381_0,
author = {Cambazard, Hadrien and Jussien, Narendra},
title = {Des explications pour reconna{\^\i}tre et exploiter les structures cach\'ees d'un probl\`eme combinatoire},
journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
pages = {381--401},
publisher = {EDP-Sciences},
volume = {40},
number = {4},
year = {2006},
doi = {10.1051/ro:2007004},
language = {fr},
url = {http://www.numdam.org/articles/10.1051/ro:2007004/}
}
TY - JOUR AU - Cambazard, Hadrien AU - Jussien, Narendra TI - Des explications pour reconnaître et exploiter les structures cachées d'un problème combinatoire JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2006 SP - 381 EP - 401 VL - 40 IS - 4 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro:2007004/ DO - 10.1051/ro:2007004 LA - fr ID - RO_2006__40_4_381_0 ER -
%0 Journal Article %A Cambazard, Hadrien %A Jussien, Narendra %T Des explications pour reconnaître et exploiter les structures cachées d'un problème combinatoire %J RAIRO - Operations Research - Recherche Opérationnelle %D 2006 %P 381-401 %V 40 %N 4 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro:2007004/ %R 10.1051/ro:2007004 %G fr %F RO_2006__40_4_381_0
Cambazard, Hadrien; Jussien, Narendra. Des explications pour reconnaître et exploiter les structures cachées d'un problème combinatoire. RAIRO - Operations Research - Recherche Opérationnelle, Tome 40 (2006) no. 4, pp. 381-401. doi : 10.1051/ro:2007004. http://www.numdam.org/articles/10.1051/ro:2007004/
[1] ,,,, and, Random constraint satisfaction: a more accurate picture, in Proceedings CP 1997, Linz, Austria (1997) 121-135.
[2] , Partitionning procedures for solving mixed-variables programming problems. Numer. Math. 4 (1962) 238-252. | Zbl
[3] , and, Neighborhood-based variable ordering heuristics for the constraint satisfaction problem, in Proceeding CP'01, Paphos, Cyprus (2001) 565-569. Short paper. | Zbl
[4] and, MAC and Combined Heuristics: Two Reasons to Forsake FC (and CBJ?) on Hard Problems, in Proceeding CP'96 (1996) 61-75.
[5] ,, and, Boosting systematic search by weighting constraints, in Proceedings ECAI'04 (2004) 482-486.
[6] ,,, and, Radio Link Frequency Assignment. Constraints 4 (1999) 79-89. | Zbl
[7] ,,, and, Decomposition and learning for a real time task allocation problem, in Proceedings CP 2004 (2004) 153-167.
[8] and, Integrating Benders decomposition within Constraint Programming, in Proceedings CP 2005 (2005) 752-756. Short paper.
[9] , and, Disjunctive learning with a soft-clustering method, in ILP'03:13th International Conference on Inductive Logic Programming, LNCS, September (2003) 75-92.
[10] , Generalized Benders Decomposition. J. Optim. Theory Practice 10 (1972) 237-260. | Zbl
[11] , and, VISEXP: visualizing constraint solver dynamics using explanations, in Proceedings FLAIRS'04, Miami, Florida, USA, May (2004) 263-268.
[12] , B.t Selman and N. Crato, Heavy-tailed distributions in combinatorial search, in Proceeding CP 97, Linz, Austria (1997) 121-135.
[13] and, Increasing tree search efficiency for constraint satisfaction problems. Artificial intelligence 14 (1980) 263-313.
[14] and, Logic-based benders decomposition. Math. Program. 96 (2003) 33-60. | Zbl
[15] and, Algorithms for hybrid MILP/CP models for a class of optimization problems. Informs J. Comput. 13 (2001) 258-276.
[16] , The versatility of using explanations within constraint programming. Habilitation thesis, Université de Nantes, France, also available as RR-03-04 research report at École des Mines de Nantes (2003).
[17] and, The PaLM system: explanation-based constraint programming, in Proceedings of TRICS: Techniques foR Implementing Constraint programming Systems, a post-conference workshop of CP 2000, Singapore (2000) 118-133.
[18] , and, Maintaining arc-consistency within dynamic backtracking, in Proceedings CP 2000, edited by R. Dechter, Singapore (2000) 249-261. | Zbl
[19] and, Local search with constraint propagation and conflict-based heuristics. Artificial Intelligence 139 (2002) 21-45. | Zbl
[20] ,,, and, Determining computational complexity for characteristic ‘phase transitions', in Nature 400 (1999) 133-137.
[21] , MAC-CBJ: maintaining arc-consistency with conflict-directed backjumping. Research report 95/177, Department of Computer Science - University of Strathclyde (2005).
[22] , and, Singleton consistencies, in Proceedings CP 2000, edited by R. Dechter, Singapore (2000) 353-368. | Zbl
[23] , Impact-based search strategies for constraint programming, in Proceedings CP 2004, Toronto, Canada (2004) 556-571.
[24] , A filtering algorithm for constraints of difference in CSPs, in AAAI 94, Twelth National Conference on Artificial Intelligence, Seattle, Washington (1994) 362-367.
[25] , and, On the connections between backdoors and heavy-tails on combinatorial search, in the International Conference on Theory and Applications of Satisfiability Testing (SAT) (2003).
[26] Ryan Williams, Carla P. Gomes, and Bart Selman. Backdoors to typical case complexity, in Proceedings IJCAI 2003 (2003).
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