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In Constraint Programming, selection of a variable and a value of its domain enumeration strategies are crucial for resolution performances. We propose to use a Choice Function for guiding enumeration: we exploit search process features to dynamically adapt a Constraint Programming solver in order to more efficiently solve Constraint Satisfaction Problems. The Choice Function provides guidance to...
This work is focused on the Enumeration phase of Constraint Programming to solve Constraint Satisfaction Problems, an enumeration strategy is constituted by a variable selection heuristic and a value selection heuristic. A suitable definition and use of the enumeration strategy can strongly improve the resolution process. In order to select the enumeration strategies dynamically here we present a...
In this work we exploit search process features to dynamically adapt a constraint programming solver in order to more efficiently solve constraint satisfaction problems. The main novelty of our approach is that we reconfigure the searching or search process based solely on performance data gathered while solving the current problem. We report encouraging results where our combination of strategies...
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