A hyperheuristic approach to select enumeration strategies in constraint programming

Authors:
Broderick Crawford;Mauricio Montecinos;Carlos Castro;Eric Monfroy
Affiliations:
Pontificia Universidad, Católica de Valparaíso, Valparaíso, Chile;Pontificia Universidad, Católica de Valparaíso, Valparaíso, Chile;Universidad Técnica, Federico Santa María, Valparaíso, Chile;Université de Nantes, Nantes, France
Venue:
AIC'09 Proceedings of the 9th WSEAS international conference on Applied informatics and communications
Year:
2009

Citing 5
Cited 0

Limited assignments: a new cutoff strategy for incomplete depth-first search

Proceedings of the 2005 ACM symposium on Applied computing
Principles of Constraint Programming

Principles of Constraint Programming
Experimental studies of variable selection strategies based on constraint weights

Journal of Algorithms
Value ordering for finding all solutions

IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Adaptive enumeration strategies and metabacktracks for constraint solving

ADVIS'06 Proceedings of the 4th international conference on Advances in Information Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this work we exploit search process features to dynamically adapt a Constraint Programming solver in order to more efficiently solve Constraint Satisfaction Problems. Our proposal uses a hyperheuristic to decide adaptation possibilities. The main novelty of our approach is that we reconfigure the search based solely on performance data gathered while solving the current problem. We report encouraging results where our combination of strategies outperforms the use of individual strategies.