On the idea of evolving decision matrix hyper-heuristics for solving constraint satisfaction problems

Authors:
José Carlos Ortiz-Bayliss;Hugo Terashima-Marín;Ender Özcan;Andrew J. Parkes
Affiliations:
Tecnológico de Monterrey, Monterrey, Mexico;Tecnológico de Monterrey, Monterrey, Mexico;University of Nottingham, Nottingham, United Kingdom;University of Nottingham, Nottingham, United Kingdom
Venue:
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Year:
2011

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Abstract

When solving a Constraint Satisfaction Problem (CSP), the order in which the variables are selected to be instantiated has implications in the complexity of the search. This work presents the first ideas for evolving hyper-heuristics as decision matrices where the elements in the matrix represent the variable ordering heuristic to apply according to the constraint density and tightness of the current instance.