Variable Ordering and Constraint Propagation for Constrained CP-Nets

  • Eisa Alanazi
  • Malek Mouhoub
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8482)


In many real world applications we are often required to manage constraints and preferences in an efficient way. The goal here is to select one or more scenarios that are feasible according to the constraints while maximizing a given utility function. This problem can be modeled as a constrained Conditional Preference Networks (Constrained CP-Nets) where preferences and constraints are represented through CP-Nets and Constraint Satisfaction Problems respectively. This problem has gained a considerable attention recently and has been tackled using backtrack search. However, there has been no study about the effect of variable ordering heuristics and constraint propagation on the performance of the backtrack search solving method. We investigate several constraint propagation strategies over the CP-Net structure while adopting the most constrained heuristic for variables ordering during search. In order to assess the effect of constraint propagation and variable ordering on the time performance of the backtrack search, we conducted an experimental study on several constrained CP-Net instances randomly generated using the RB model. The results of these experiments clearly show a significant improvement when compared to the well known methods for solving constrained CP-Nets.


Constraint Satisfaction Problem Constraint Propagation Pareto Solution Backtrack Search Forward Check 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Eisa Alanazi
    • 1
  • Malek Mouhoub
    • 1
  1. 1.Department of Computer ScienceUniversity of ReginaReginaCanada

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