Efficient search techniques—an empirical study of the N-Queens problem
IBM Journal of Research and Development
A dynamic constraint-directed ordered search algorithm for solving constraint satisfaction problems
IEA/AIE '88 Proceedings of the 1st international conference on Industrial and engineering applications of artificial intelligence and expert systems - Volume 1
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
New methods to color the vertices of a graph
Communications of the ACM
Synthesizing constraint expressions
Communications of the ACM
Backtrack programming techniques
Communications of the ACM
Hyperheuristics: A Robust Optimisation Method Applied to Nurse Scheduling
PPSN VII Proceedings of the 7th International Conference on Parallel Problem Solving from Nature
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
Selecting the Right Heuristic Algorithm: Runtime Performance Predictors
AI '96 Proceedings of the 11th Biennial Conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence
A comprehensive analysis of hyper-heuristics
Intelligent Data Analysis
Hyper-heuristics for the dynamic variable ordering in constraint satisfaction problems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Where the really hard problems are
IJCAI'91 Proceedings of the 12th international joint conference on Artificial intelligence - Volume 1
Search rearrangement backtracking and polynomial average time
Artificial Intelligence
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Analysis of heuristic synergies
CSCLP'05 Proceedings of the 2005 Joint ERCIM/CoLogNET international conference on Constraint Solving and Constraint Logic Programming
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Hyper-heuristics enable us to selectively apply the most suitable low-level heuristic depending on the properties of the problem at hand. They can be used for solving Constraint Satisfaction Problems (CSP) in different ways considering the variety of hyper-heuristics and low-level heuristics. A particular approach which has been receiving attention in the recent years is based on variable ordering using hyper-heuristics. A hyper-heuristic decides the next variable to process using a set of predefined heuristics considering the features that describe the instance at a given point during the search in this framework. This study explores an approach in which each hyper-heuristic is represented as a set of vectors mapping instance features to heuristics for variable ordering. The results suggest that the proposed approach is able to combine the strengths of different heuristics and compensate for their weaknesses performing better than each heuristic in isolation across a range of instances.