Abstract
The contribution of this paper is twofold. On the one hand, it introduces a concept of fac variables in discrete Constraint Satisfaction Problems (CSPs). fac variables can be discovered by local search techniques and powerfully exploited by MAC-based methods. On the other hand, a novel synergetic combination schema between local search paradigms, generalized arc-consistency and MAC-based algorithms is presented. By orchestrating a multiple-way flow of information between these various fully integrated search components, it often proves more competitive than the usual techniques on most classes of instances.
Part of this work was supported by the French Ministry of Higher Education and Research, Nord/Pas-de-Calais Regional Council and E.C. FEDER program through the ‘Contrat de Projets État/Région (CPER) 2007-2013’ and by the French National Research Agency (ANR) through the UNLOC and TUPLES projects.
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References
Audemard, G., Lagniez, J.M., Mazure, B., Saïs, L.: Boosting local search thanks to CDCL. In: Fermüller, C.G., Voronkov, A. (eds.) LPAR-17. LNCS, vol. 6397, pp. 474–488. Springer, Heidelberg (2010)
Bessière, C., Régin, J.C., Yap, R., Zhang, Y.: An optimal coarse-grained arc consistency algorithm. Artificial Intelligence 165(2), 165–185 (2005)
Boussemart, F., Hemery, F., Lecoutre, C., Saïs, L.: Boosting systematic search by weighting constraints. In: ECAI 2004, pp. 146–150 (2004)
Cheeseman, P., Kanefsky, B., Taylor, W.: Where the really hard problems are. In: IJCAI 1991, pp. 331–340 (1991)
Third international CSP solver competition (2008), http://cpai.ucc.ie/08/
Fourth international CSP solver competition (2009), http://cpai.ucc.ie/09/
Eisenberg, C., Faltings, B.: Making the breakout algorithm complete using systematic search. In: IJCAI 2003, pp. 1374–1375 (2003)
Eisenberg, C., Faltings, B.: Using the breakout algorithm to identify hard and unsolvable subproblems. In: Rossi, F. (ed.) CP 2003. LNCS, vol. 2833, pp. 822–826. Springer, Heidelberg (2003)
Eiter, T., Gottlob, G.: On the complexity of propositional knowledge base revision, updates and counterfactuals. Artificial Intelligence 57, 227–270 (1992)
Galinier, P., Hao, J.K.: Tabu search for maximal constraint satisfaction problems. In: Smolka, G. (ed.) CP 1997. LNCS, vol. 1330, pp. 196–208. Springer, Heidelberg (1997)
Gégoire, É., Mazure, B., Piette, C.: Local-search extraction of muses. Constraints 12(3), 325–344 (2007)
Goldberg, E.: Boundary points and resolution. In: Kullmann, O. (ed.) SAT 2009. LNCS, vol. 5584, pp. 147–160. Springer, Heidelberg (2009)
Gu, J.: Design efficient local search algorithms. In: Belli, F., Radermacher, F.J. (eds.) IEA/AIE 1992. LNCS, vol. 604, pp. 651–654. Springer, Heidelberg (1992)
Hébrard, E.: Mistral 1.529 (2006), http://4c.ucc.ie/~ehebrard/mistral/doxygen/html/main.html
Hoos, H.: An adaptive noise mechanism for walksat. In: AAAI 2002, pp. 655–660 (2002)
Jussien, N., Lhomme, O.: Combining constraint programming and local search to design new powerful heuristics. In: MIC 2003 (2003)
Kirkpatrick, S., Gelatt Jr., D., Vecchi, M.: Optimization by simulated annealing. Science 220(4598), 671–680 (1983)
Lecoutre, C., Hemery, F.: A study of residual supports in arc consistency. In: IJCAI 2007, pp. 125–130 (2007)
Lecoutre, C., Tabary, S.: Abscon 112: towards more robustness. In: CSC 2008, pp. 41–48 (2008)
Mackworth, A.: Consistency in networks of relations. Artificial Intelligence 8(1), 99–118 (1977)
Mazure, B., Saïs, L., Grégoire, É.: Boosting complete techniques thanks to local search methods. Annals of Mathematics and Artificial Intelligence 22(3-4), 319–331 (1998)
McAllester, D., Selman, B., Kautz, H.: Evidence for invariants in local search. In: AAAI 1997, pp. 321–326 (1997)
Merchez, S., Lecoutre, C., Boussemart, F.: Abscon: A prototype to solve CSPs with abstraction. In: Walsh, T. (ed.) CP 2001. LNCS, vol. 2239, pp. 730–744. Springer, Heidelberg (2001)
Minton, S., Johnston, M., Philips, A., Laird, P.: Minimizing conflicts: A heuristic repair method for constraint satisfaction and scheduling problems. Artificial Intelligence 58(1-3), 161–205 (1992)
Sabin, D., Freuder, E.: Contradicting conventional wisdom in constraint satisfaction. In: ECAI 1994, pp. 125–129 (1994)
Selman, B., Kautz, H., Cohen, B.: Noise strategies for improving local search. In: AAAI 1994, pp. 337–343 (1994)
Selman, B., Levesque, H., Mitchell, D.: A new method for solving hard satisfiability problems. In: AAAI 1992, pp. 440–446 (1992)
Tamura, N., Taga, A., Kitagawa, S., Banbara, M.: Compiling finite linear CSP into SAT. Constraints 14(2), 254–272 (2009)
Choco Team. Choco: an open source Java constraint programming library. Research report 10-02-INFO, Ecole des Mines de Nantes (2010)
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Grégoire, É., Lagniez, JM., Mazure, B. (2011). A CSP Solver Focusing on fac Variables. In: Lee, J. (eds) Principles and Practice of Constraint Programming – CP 2011. CP 2011. Lecture Notes in Computer Science, vol 6876. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23786-7_38
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