Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Boosting complete techniques thanks to local search methods
Annals of Mathematics and Artificial Intelligence
Finding the Right Hybrid Algorithm – A Combinatorial Meta-Problem
Annals of Mathematics and Artificial Intelligence
A Constraint Programming Framework for Local Search Methods
Journal of Heuristics
Heuristics for Large Constrained Vehicle Routing Problems
Journal of Heuristics
Using Constraint-Based Operators to Solve the Vehicle Routing Problem with Time Windows
Journal of Heuristics
A Constraint-Based Method for Project Scheduling with Time Windows
Journal of Heuristics
Heuristic Constraint Propagation
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Local Probing Applied to Scheduling
CP '02 Proceedings of the 8th International Conference on Principles and Practice of Constraint Programming
Interaction of Constraint Programming and Local Search for Optimisation Problems
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Metaheuristics in combinatorial optimization: Overview and conceptual comparison
ACM Computing Surveys (CSUR)
Combining local and global search in a constraint programming environment
The Knowledge Engineering Review
A Two-Stage Hybrid Local Search for the Vehicle Routing Problem with Time Windows
Transportation Science
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Enhancements of branch and bound methods for the maximal constraint satisfaction problem
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Evolutionary approach for automated component-based decision tree algorithm design
Intelligent Data Analysis - Business Analytics and Intelligent Optimization
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Backtrack search enhanced by local consistency techniques can be effective at finding solutions for (or proving the infeasibility of) tightly-constrained problems with complex and overlapping constraints. By contrast, local search can be superior at optimizing problems that are loosely constrained, but is weaker on problems with a complex constraint satisfaction element, and cannot prove problem infeasibility. This paper describes local probing which marries the strengths of local search and backtrack search and is capable of finding a solution or proving that none exists. Local probing is a local search extension to an existing hybridization framework, probe backtrack search. Here, a master backtrack search algorithm hybridizes a slave local search algorithm, which solves dynamically created subproblems that are easier to solve than the original problem addressed. We present comparison results on resource constrained scheduling, showing how local probing successfully adds infeasibility proofs to its slave local search algorithm.