Integer and combinatorial optimization
Integer and combinatorial optimization
An efficient algorithm for finding a maximum weight 2-independent set on interval graphs
Information Processing Letters
Cutting Planes in Constraint Programming: A Hybrid Approach
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)
Lagrangian Cardinality Cuts and Variable Fixing for Capacitated Network Design
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Shorter path constraints for the resource constrained shortest path problem
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
A totally unimodular description of the consistent value polytope for binary constraint programming
CPAIOR'06 Proceedings of the Third international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
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Variable fixing is an important technique when solving combinatorial optimization problems. Unique profitable variable values are detected with respect to the objective function and to the constraint structure of the problem. Relying on that specific structure, effective variable fixing algorithms (VFAs) are only suited for the problems they have been designed for. Frequently, new combinatorial optimization problems evolve as a combination of simpler structured problems. For such combinations, we show how VFAs for linear optimization problems can be coupled via Lagrangian relaxation. The method is applied on a multimedia problem incorporating a knapsack and a maximum weighted stable set problem.