An extensible autonomous search framework for constraint programming

Broderick Crawford, Ricardo Soto, Carlos Castro, Eric Monfroy, Fernando Paredes

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


Constraint programming is a modern programming paradigm devoted to solve constraint-based problems, in particular combinatorial problems. In this paradigm, the efficiency on the solving process is the key, which generally depends on the selection of suitable search strategies. However, determining a good search strategy is quite difficult, as its effects on the solving process are hard to predict. A novel solution to handle this concern is called autonomous search, which is a special feature allowing an automatic reconfiguration of the solving process when a poor performance is detected. In this paper, we present an extensible architecture for performing autonomous search in a constraint programming context. The idea is to carry out an "on the fly" replacement of bad-performing strategies by more promising ones. We report encouraging results where the use of autonomous search in the resolution outperforms the use of individual strategies.

Original languageEnglish
Pages (from-to)3369-3376
Number of pages8
JournalInternational Journal of Physical Sciences
Issue number14
StatePublished - 18 Jul 2011


  • Autonomous search
  • Constraint programming
  • Heuristic search


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