Possibilistic constraint satisfaction problems or “how to handle soft constraints?”
UAI '92 Proceedings of the eighth conference on Uncertainty in Artificial Intelligence
Computers and Operations Research
Maintaining reversible DAC for Max-CSP
Artificial Intelligence
Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, Workshop, October 11-13, 1993
Radio Link Frequency Assignment
Constraints
Earth Observation Satellite Management
Constraints
Variable Neighborhood Decomposition Search
Journal of Heuristics
Using Constraint Programming and Local Search Methods to Solve Vehicle Routing Problems
CP '98 Proceedings of the 4th International Conference on Principles and Practice of Constraint Programming
Intelligent variable orderings and re-orderings in DAC-based solvers for WCSP
Journal of Heuristics
On-line resources allocation for ATM networks with rerouting
Computers and Operations Research
Exploiting tree decomposition and soft local consistency in weighted CSP
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
An algorithm for optimal winner determination in combinatorial auctions
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Valued constraint satisfaction problems: hard and easy problems
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
In the quest of the best form of local consistency for weighted CSP
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Solving constraint optimization problems in anytime contexts
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
The partial constraint satisfaction problem: Facets and lifting theorems
Operations Research Letters
Intensification/Diversification-Driven ILS for a graph coloring problem
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
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Weighted CSP (Constraint Satisfaction Problems) are used to model and to solve constraint optimization problems. As most WCSP are solved by local search methods that use large neighborhoods, selecting the neighborhood to explore is crucial. However, designing efficient neighborhoods is difficult and problem dependent. The very few generic heuristics defined for CSP, as ConflictVar or H-PGLNS, are not well suited for WCSP. In this paper, we propose new generic neighborhood heuristics dedicated to WCSP. Our heuristics take advantage of both conflicted variables and the topology of the constraints graph. We define the concept of freedom degree of a variable to make a compromise between these two criteria, and introduce a diversification criterion by choosing non-conflicted variables connected to conflicted ones. Then we extend, in a systematic way, each proposed heuristic in order to take into account violation costs of constraints. Experiments have been performed on real life instances (RLFAP) as well as random instances (GRAPH and Kbtree) using VNS/LDS+CP (a particular instance of VNS we developed). Experiments show that our generic heuristics clearly outperform ConflictVar and H-PGLNS. Among all topological heuristics we proposed, ConflictVar-MaxDeg appears to be the best one.