Authors:
Maximilian Bels
;
Sven Löffler
;
Ilja Becker
and
Petra Hofstedt
Affiliation:
Programming Languages and Compilers Group, Brandenburg University of Technology, Konrad-Wachsmann-Allee 5, Cottbus, Germany
Keyword(s):
Constraint Programming, Finite-Domain Constraint Satisfaction Problem, CSP, Search Tree, Constraint-Based Filtering.
Abstract:
Using Constraint Programming (CP) real world problems can be described conveniently in a declarative way with constraints in a so-called constraint satisfaction problem (CSP). Finite domain CSPs (FD-CSPs) are one form of CSPs, where the domains of the variables are finite. Such FD-CSPs are mostly evaluated by a search nested with propagation, where the search process can be represented by search trees. Since search can quickly become very time-consuming, especially with large variable domains (solving CSPs is NP-hard in general), heuristics are used to control the search, which in many cases — depending on the problem — allow to achieve a performance gain. In this paper, we present a new method for filtering and evaluating search trees of FD-CSPs. Our new tree filtering method is based on the idea of formulating and evaluating filters as constraints over FD-CSP search trees. The constraint-based formulation of filter criteria proves to be very flexible. Our new technique was integrat
ed into the Visual Constraint Solver (VCS) tool, which allows the solution process of CSPs to be followed interactively and step by step through a suitable visualization.
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