Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
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
A Constraint-Based Method for Project Scheduling with Time Windows
Journal of Heuristics
Local Search with Constraint Propagation and Conflict-Based Heuristics
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
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
Combine and Conquer: Genetic Algorithm and CP for Optimization
CP '98 Proceedings of the 4th International Conference on Principles and Practice of Constraint Programming
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IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Combining local search and backtracking techniques for constraint satisfaction
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
A framework for constructing complete algorithms based on local search
AI Communications - Constraint Programming for Planning and Scheduling
Hybrid algorithms in constraint programming
CSCLP'06 Proceedings of the constraint solving and contraint logic programming 11th annual ERCIM international conference on Recent advances in constraints
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Thisp aper describes local probing, an algorithm hybridization form that combines backtrack search enhanced with local consistency techniques(B T+CS) with local search (LS) via probe backtracking. Generally BT+CS can be effective at finding solutions for (or proving the infeasibility of) tightly constrained problems with complex and overlapping constraints, but lacks good optimization characteristics. By contrast, LS can be superior at optimizing problems that are loosely constrained, or that have constraints which are satisfiable by simple neighbourhood procedures, but it also has several weaknesses of its own. It is weaker on problems with a complex constraint satisfaction element, and cannot prove problem infeasibility, causing prolonged execution times and ambiguous search outcomes for even trivially infeasible problems. We show these divergent characteristics on a general resource constrained scheduling problem class, extended with a widely applicable objective function.We then detail a local probing hybrid that marriesthe strengths of constraint satisfaction techniques, including good satisfaction characteristics and proofs of problem infeasibility, with the superior optimization characteristics of LS. This local probing hybrid achieves sat-completeness, without incorporating all the constraints into the LS neighbourhood function. Finally, we discuss the principal questions that must be answered in creating local probing hybrids for other problems.