A Hybrid Approach for the Sudoku Problem: Using Constraint Programming in Iterated Local Search

Sudoku is not only a popular puzzle but also an interesting and challenging constraint satisfaction problem. Therefore, automatic solving methods have been the subject of several publications in the past two decades. Although current methods provide good solutions for small-sized puzzles, larger instances remain challenging. This article introduces a new local search technique based on the min-conflicts heuristic for Sudoku. Furthermore, the authors propose an innovative hybrid search technique that exploits constraint programming as a perturbation technique within the iterated local search framework. They experimentally evaluate their methods on challenging benchmarks for Sudoku and report improvements over state-of-the-art solutions. To show the generalizability of the proposed approach, they also applied their method on another challenging scheduling problem. The results show that the proposed method is also robust in another problem domain.