A High Level Language for Solver Independent Model Manipulation and Generation of Hybrid Solvers

  • Daniel Fontaine
  • Laurent Michel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7298)


This paper introduces a high level language that allows for the specification and manipulation of solver independent models and allows for easily generating complex solvers in the Comet language. As Constraint Programming (CP) techniques have increased in complexity, it has become more difficult and time consuming to implement models that take advantage of state-of-the-art modeling techniques and search heuristics. This is particularly problematic for problems that have not been well studied as it is often unclear a priori which modeling technologies and search strategies will be effective.

This work builds on previous solver independent languages by introducing a more general framework based on abstract models and model operators. Model operators represent complex model transformations that can be applied in various combinations to yield a wide array of concrete solvers, including hybrid solvers. Furthermore, Local Search (LS) is fully supported allowing for sequential and parallel bounds-passing hybrids that have not been possible in previous solver independent languages. Large Neighborhood Search (LNS) and column generation based models are also demonstrated.


Column Generation Constraint Programming Master Problem High Level Language Hybrid Solver 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Akgun, O., Miguel, I., Jefferson, C., Frisch, A., Hnich, B.: Extensible automated constraint modelling (2011)Google Scholar
  2. 2.
    Baatar, D., Boland, N., Brand, S., Stuckey, P.: Minimum Cardinality Matrix Decomposition into Consecutive-Ones Matrices: CP and IP Approaches. In: Van Hentenryck, P., Wolsey, L. (eds.) CPAIOR 2007. LNCS, vol. 4510, pp. 1–15. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  3. 3.
    Daniel Fontaine, L.M.: A large-scale neighborhood search approach to matrix decomposition into consecutive-ones matrices. In: 8th Workshop on Local Search Techniques in Constraint Satisfaction, vol. 9 (2011)Google Scholar
  4. 4.
    Duck, G.J., De Koninck, L., Stuckey, P.J.: Cadmium: An Implementation of ACD Term Rewriting. In: Garcia de la Banda, M., Pontelli, E. (eds.) ICLP 2008. LNCS, vol. 5366, pp. 531–545. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  5. 5.
    Duck, G.J., Stuckey, P.J., Brand, S.: ACD Term Rewriting. In: Etalle, S., Truszczyński, M. (eds.) ICLP 2006. LNCS, vol. 4079, pp. 117–131. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Frisch, A., Harvey, W., Jefferson, C., Martínez-Hernández, B., Miguel, I.: Essence: A constraint language for specifying combinatorial problems. Constraints 13, 268–306 (2008)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Moura, L.D., Passmore, G.O.: The strategy challenge in smt solvingGoogle Scholar
  8. 8.
    Perron, L., Shaw, P., Furnon, V.: Propagation Guided Large Neighborhood Search. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 468–481. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  9. 9.
    Puchinger, J., Stuckey, P.J., Wallace, M., Brand, S.: From High-Level Model to Branch-and-Price Solution in G12. In: Perron, L., Trick, M. (eds.) CPAIOR 2008. LNCS, vol. 5015, pp. 218–232. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  10. 10.
    Puchinger, J., Stuckey, P., Wallace, M., Brand, S.: Dantzig-wolfe decomposition and branch-and-price solving in g12. Constraints 16, 77–99 (2011)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Refalo, P.: Linear Formulation of Constraint Programming Models and Hybrid Solvers. In: Dechter, R. (ed.) CP 2000. LNCS, vol. 1894, pp. 369–383. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  12. 12.
    Refalo, P.: Impact-Based Search Strategies for Constraint Programming. In: Wallace, M. (ed.) CP 2004. LNCS, vol. 3258, pp. 557–571. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  13. 13.
    Schrijvers, T., Tack, G., Wuille, P., Samulowitz, H., Stuckey, P.J.: Search Combinators. In: Lee, J. (ed.) CP 2011. LNCS, vol. 6876, pp. 774–788. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  14. 14.
    Shaw, P.: Using constraint programming and local search methods to solve vehicle routing problems, pp. 417–431. Springer, Heidelberg (1998)Google Scholar
  15. 15.
    Stuckey, P.J., de la Banda, M.G., Maher, M., Marriott, K., Slaney, J., Somogyi, Z., Wallace, M., Walsh, T.: The G12 Project: Mapping Solver Independent Models to Efficient Solutions. In: Gabbrielli, M., Gupta, G. (eds.) ICLP 2005. LNCS, vol. 3668, pp. 9–13. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  16. 16.
    Van Hentenryck, L., Michel, P.: Synthesis of constraint-based local search algorithms from high-level models. In: Proceedings of the National Conference on Artificial Intelligence, vol. 1(CONF 22), pp. 273–279 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Daniel Fontaine
    • 1
  • Laurent Michel
    • 1
  1. 1.University of ConnecticutStorrsUSA

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