Solving Constraint Satisfaction Puzzles with Constraint Programming

Abstract

Constraint Programming (CP) is a powerful paradigm for solving Combinatorial Problems (generally issued from Decision Making). In CP, Enumeration Strategies are crucial for resolution performances. In this work, we model the known benchmark problems Latin Square, Magic Square and Sudoku as a Constraint Satisfaction Problems. We solve them with Constraint Programming comparing the performance of di erent Variable and Value Selection Heuristics in its Enumeration phase. The platform used was Mozart