Solving Functional Constraints by Variable Substitution
Zhang, Yuanlin, Yap, Roland H. C.
–arXiv.org Artificial Intelligence
Functional constraints and bi-functional constraints are an important constraint class in Constraint Programming (CP) systems, in particular for Constraint Logic Programming (CLP) systems. CP systems with finite domain constraints usually employ CSP-based solvers which use local consistency, for example, arc consistency. We introduce a new approach which is based instead on variable substitution. We obtain efficient algorithms for reducing systems involving functional and bi-functional constraints together with other nonfunctional constraints. It also solves globally any CSP where there exists a variable such that any other variable is reachable from it through a sequence of functional constraints. Our experiments on random problems show that variable elimination can significantly improve the efficiency of solving problems with functional constraints. To appear in Theory and Practice of Logic Programming (TPLP).
arXiv.org Artificial Intelligence
Jun-16-2010
- Country:
- Asia > Singapore (0.04)
- North America > United States
- Texas (0.04)
- Genre:
- Research Report > New Finding (0.46)
- Technology: