A Hyperheuristic Approach for Guiding Enumeration in Constraint Solving Broderick Crawford, Carlos Castro, Eric Monfroy, Ricardo Soto, Wenceslao Palma, and Fernando Paredes Abstract. In this paper we design and evaluate a dynamic selection mechanism of enumeration strategies based on the information of the solving process. Unlike pre- vious research works we focus in reacting on the fly, allowing an early replacement of bad-performance strategies without waiting the entire solution process or an ex- haustive analysis of a given class of problems. Our approach uses a hyperheuristic approach that operates at a higher level of abstraction than the Constraint Satis- faction Problems solver. The hyperheuristic has no problem-specific knowledge. It manages a portfolio of enumeration strategies. At any given time the hyperheuristic must choose which enumeration strategy to call. The experimental results show the effectiveness of our approach where our combination of strategies outperforms the use of individual strategies. 1 Introduction Constraint Programming (CP) is a powerful software technology devoted to the efficient resolution of constraint-based problems. Currently, CP is largely used in Broderick Crawford · Ricardo Soto Pontificia Universidad Cat´ olica de Valpara´ ıso, Chile e-mail: broderick.crawford@ucv.cl Carlos Castro Universidad T´ ecnica Federico Santa Mar´ ıa, Chile e-mail: carlos.castro@inf.utfsm.cl,ricardo.soto@ucv.cl Eric Monfroy CNRS, LINA, Universit´ e de Nantes, France e-mail: ericmonfroy@gmail.com Wenceslao Palma Pontificia Universidad Cat´ olica de Valpara´ ıso, Chile e-mail: wenceslao.palma@ucv.cl Fernando Paredes Escuela de Ingenier´ ıa Industrial, Universidad Diego Portales, Santiago, Chile e-mail: fernando.paredes@udp.cl O. Sch ¨ utze et al. (Eds.): EVOLVE – A Bridge between Probability, AISC 175, pp. 171–188. springerlink.com c  Springer-Verlag Berlin Heidelberg 2013