Combining Metaheuristics and CSP Algorithms to Solve Sudoku

Abstract

Sudoku is a very popular puzzle game that is played by millions of people everyday. In spite of that, it is a NP-Hard problem that can be very difficult to solve depending on the initial conditions of the board. In this paper, we propose the combination of metaheuristics with techniques from the Constraint Satisfaction Problem (CSP) domain that speed up the solution's search process by decreasing its search space and its processing time. Experiments performed with boards of size 3, 4 and 5 show that this approach allows the resolution of a greater number of instances when compared to an initial baseline.