Finding crucial subproblems to focus global search

Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI

Volumn , Issue , 2006, Pages 151-159

  Epstein, Susan L ^a   Wallace, Richard J ^b  

^a CITY UNIVERSITY OF NEW YORK   (United States)

^b UNIVERSITY COLLEGE CORK   (Ireland)

Author keywords

[No Author keywords available]

Indexed keywords

GLOBAL SEARCH; STRUCTURED PROBLEMS;

PROBLEM SOLVING; TABU SEARCH;

HEURISTIC METHODS;

EID: 38949184557     PISSN: 10823409     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICTAI.2006.60     Document Type: Conference Paper

References (21)

1. Williams, R., C. Gomes and B. Selman. On the Connections between Heavy-tails, Backdoors, and Restarts in Combinatorial search. In the Proceedings of SAT 2003. 2003.
2. Dechter, R. and J. Pearl. The cycle-cutset method for improving search performance. In the Proceedings of Third Conference on Artificial Intelligence Applications. 1987. p. 224-230.
3. Hansen, P. and N. Mladenovic, Variable Neighborhood Search, in Handbook of Metaheuristics, F. W. Glover and G. A. Kochenberger, Editors. 2003, Springer: Berlin.
4. Bessière, C. and J.-C. Régin. Enforcing arc consistency on global constraints by solving subproblems on the fly. In the Proceedings of Fifth International Conference on Principles and Practice of Constraint Programming (CP-99). 1999. p. 103-117.
5. van Hoeve, W. J. and I. Katriel, Global Constraints, in Handbook of Constraint Programming, F. Rossi, P. Van Beek and T. Walsh, Editors. 2006: Prague.
6. Hallodórsson, M. M. and H. C. Lau, Low-degree Graph Partitioning via Local Search with Applications to Constraint Satisfaction, Max Cut, and Coloring. Journal of Graph Algorithms and Applications, 1997. 1(3): p. 1-13.
7. Eisenberg, C. and B. Faltings. Using the Breakout Algorithm to Identify Hard and Unsolvable Subproblems. In the Proceedings of Principles and Practice of Constraint Programming CP-2003, LNCS 2833. 2003: Springer Verlag, p. 822-826.
8. Beale, S., S. Nirenburg and K. Mahesh. HUNTER-GATHERER: Three Search Techniques Integrated for Natural Language Semantics. In the Proceedings of AAAI-96. 1996. Portland: AAAI. p. 1056-1061.
9. Aardal, K. I., S. P. M. van Hoesel, A. M. C. A. Koster, C. Mannino and A. Sassano, Models and solution techniques for frequency assignment problems. 4OR: A Quarterly Journal of Operations Research, 2003. 1(4): p. 261-317.
10. Hansen, P., N. Mladenovic and D. Urosevic, Variable neighborhood search for the maximum clique. Discrete Applied Mathematics, 2004. 145: p. 117-125.
11. Epstein, S. L., E. C. Freuder and R. J. Wallace, Learning to Support Constraint Programmers. Computational Intelligence, 2005. 21(4): p. 337-371.
12. Mackworth, A. K., Consistency in Networks of Relations. Artificial Intelligence, 1977. 8: p. 99-118.
13. Bayardo, R. J. J. and R. Schrag. Using CSP Look-Back Techniques to Solve Exceptionally Hard SAT Instances. In the Proceedings of Second International Conference on Principles and Practice of Constraint Programming CP-1996. 1996. p. 46-60.
14. Boussemart, F., F. Hemery, C. Lecoutre and L. Sais. Boosting systematic search by weighting constraints. In the Proceedings of ECAI-2004. 2004: IOS Press, p. 146-149.
15. Petrovic, S. and S. L. Epstein. Learning Weights for Heuristics that Solve Constraint Problems. In the Proceedings of Workshop on Learning to Search at AAAI-2006. 2006. Boston.
16. Johnson, D. B., C. R. Aragon, L. A. McGeooh and C. Schevon, Optimization by Simulated Annealing: An experimental evaluation; Part 1, Graph partitioning. Operations Research, 1989. 37(865-892).
17. Pearson, J. and P. G. Jeavons, A Survey of Tractable Constraint Satisfaction Problems. 1997, Royal Holloway University of London: London.
18. Dechter, R. and J. Pearl, Tree Clustering For Constraint Networks. Artificial Intelligence, 1989. 38: p. 353-366.
19. Dechter, R., Enhancement schemes for constraint processing: backjumping, learning and cutset decomposition. Artificial Intelligence, 1990. 41: p. 273-312.
20. Gompert, J. and B. Y. Choueiry. A Decomposition Techniques For CSPs Using Maximal Independent Sets And Its Integration With Local Search. In the Proceedings of FLAIRS-05. 2005. Clearwater Beach, FL: AAAI Press.
21. Gyssens, M., P. G. Jeavons and D. A. Cohen, Decomposing constraint satisfaction problems using data-base techniques. Artificial Intelligence, 1994. 66(1): p. 57-89.