Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A constraint programming approach to cutset problems
Computers and Operations Research
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Handbook of Constraint Programming (Foundations of Artificial Intelligence)
Consistency Techniques for Finding an Optimal Relaxation of a Feature Subscription
ICTAI '08 Proceedings of the 2008 20th IEEE International Conference on Tools with Artificial Intelligence - Volume 01
Improving the Global Constraint SoftPrec
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
A generic visualization platform for CP
CP'10 Proceedings of the 16th international conference on Principles and practice of constraint programming
Developing approaches for solving a telecommunications feature subscription problem
Journal of Artificial Intelligence Research
| Hi-index | 0.00 |
Hard and soft precedence constraints play a key role in many application domains. In telecommunications, one application is the configuration of callcontrol feature subscriptions where the task is to sequence a set of user-selected features subject to a set of hard (catalogue) precedence constraints and a set of soft (user-selected) precedence constraints. When no such consistent sequence exists, the task is to find an optimal relaxation by discarding some features or user precedences. For this purpose, we present the global constraint SOFTPREC. Enforcing Generalized Arc Consistency (GAC) on SOFTPREC is NP-complete. Therefore, we approximate GAC based on domain pruning rules that follow from the semantics of SOFTPREC; this pruning is polynomial. Empirical results demonstrate that the search effort required by SOFTPREC is up to one order of magnitude less than the previously known best CP approach for the feature subscription problem. SOFTPREC is also applicable to other problem domains including minimum cutset problems for which initial experiments confirm the interest.