Deliberation scheduling for problem solving in time-constrained environments
Artificial Intelligence
Computers and Operations Research
Maintaining reversible DAC for Max-CSP
Artificial Intelligence
Monitoring and control of anytime algorithms: a dynamic programming approach
Artificial Intelligence - special issue on computational tradeoffs under bounded resources
Radio Link Frequency Assignment
Constraints
A Meta-Heuristic Factory for Vehicle Routing Problems
CP '99 Proceedings of the 5th International Conference on Principles and Practice of Constraint Programming
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
A unified framework for partial and hybrid search methods in constraint programming
Computers and Operations Research
On-line resources allocation for ATM networks with rerouting
Computers and Operations Research
Boosting VNS with Neighborhood Heuristics for Solving Constraint Optimization Problems
HM '08 Proceedings of the 5th International Workshop on Hybrid Metaheuristics
Advanced generic neighborhood heuristics for VNS
Engineering Applications of Artificial Intelligence
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This paper presents a new hybrid method for solving constraint optimization problems in anytime contexts. Discrete optimization problems are modelled as Valued CSP. Our method (VNS/LDS+CP) combines a Variable Neighborhood Search and Limited Discrepancy Search with Constraint Propagation to efficiently guide the search. Experiments on the CELAR benchmarks demonstrate significant improvements over other competing methods. VNS/LDS+CP has been successfully applied to solve a real-life anytime resource allocation problem in computer networks.