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Synthesis of Search Algorithms from High-Level CP Models

  • Samir A. Mohamed Elsayed
  • Laurent Michel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6876)

Abstract

The ability to specify CP programs in terms of a declarative model and a search procedure is instrumental to the industrial CP successes. Yet, writing search procedures is often difficult for novices or people accustomed to model & run approaches. The viewpoint adopted in this paper argues for the synthesis of a search from the declarative model to exploit the problem instance structures. The intent is not to eliminate the search. Instead, it is to have a default that performs adequately in the majority of cases while retaining the ability to write full-fledged procedures. Empirical results demonstrate that the approach is viable, yielding procedures approaching and sometimes rivaling hand-crafted searches.

Keywords

Constraint Programming Constraint Satisfaction Problem Global Constraint Default Rule Static Degree 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Samir A. Mohamed Elsayed
    • 1
  • Laurent Michel
    • 1
  1. 1.Computer Science DepartmentUniversity of ConnecticutUSA

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