Integer and combinatorial optimization
Integer and combinatorial optimization
An additive bounding procedure for the asymmetric travelling salesman problem
Mathematical Programming: Series A and B
A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Solving TSP with time windows with constraints
Proceedings of the 1999 international conference on Logic programming
Improving Branch and Bound for Jobshop Scheduling with Constraint Propagation
Selected papers from the 8th Franco-Japanese and 4th Franco-Chinese Conference on Combinatorics and Computer Science
Branch and Infer: a Unifying Framework for Integer and Finite Domain Constraint Programming
INFORMS Journal on Computing
On global warming: Flow-based soft global constraints
Journal of Heuristics
A global constraint for total weighted completion time for cumulative resources
Engineering Applications of Artificial Intelligence
A Global Constraint for Total Weighted Completion Time
CPAIOR '07 Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Cost-Based Domain Filtering for Stochastic Constraint Programming
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
The complexity of global constraints
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Agent based framework for emergency rescue and assistance planning
PAISI'07 Proceedings of the 2007 Pacific Asia conference on Intelligence and security informatics
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Discrepancy-based sliced neighborhood search
AIMSA'10 Proceedings of the 14th international conference on Artificial intelligence: methodology, systems, and applications
Improving CP-based local branching via sliced neighborhood search
Proceedings of the 2011 ACM Symposium on Applied Computing
Expert Systems with Applications: An International Journal
An a-team based architecture for constraint programming
PRIMA'06 Proceedings of the 9th Pacific Rim international conference on Agent Computing and Multi-Agent Systems
Combining arc-consistency and dual lagrangean relaxation for filtering CSPs
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Compositional derivation of symmetries for constraint satisfaction
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Bounding, filtering and diversification in CP-based local branching
Journal of Heuristics
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In this paper, we propose a way of exploiting Operations Research techniques within global constraints for cost-based domain filtering. In Constraint Programming, constraint propagation is aimed at removing from variable domains combinations of values which are proven infeasible. Pruning derives from ifeasibility reasoning. When coping with optimization problems, pruning can be performed also on the basis of costs, i.e., ioptimality reasoning. Cost-based filtering removes combination of values which are proven sub-optimal. For this purpose, we encapsulate in global constraints optimization components representing suitable relaxations of the constraint itself. These components embed efficient Operations Research algorithms computing the optimal solution of the relaxed problem and a gradient function representing the estimated cost of each variable-value assignment. We exploit these pieces of information for pruning and for guiding the search. We have applied these techniques to a couple of ILOG Solver global constraints (a constraint of difference and a path constraint) and tested the approach on a variety of combinatorial optimization problems such as Timetabling, Travelling Salesman Problems and Scheduling Problems with sequence dependent setup times. Comparisons with pure Constraint Programming approaches and related literature clearly show the benefits of the proposed approach.