A Hybrid alldifferent-Tabu Search Algorithm for Solving Sudoku Puzzles. (20th May 2015)

• Record Type: Journal Article
• Authors: Soto, Ricardo; Crawford, Broderick; Galleguillos, Cristian; Paredes, Fernando; Norero, Enrique
• Other Names: Dawson Christian W. Academic Editor.
• Is Part Of: Computational intelligence and neuroscience. Volume 2015(2015)
• Publication Date: 2015-05-20
• Subjects: Neurosciences -- Data processing -- Periodicals; Computational intelligence -- Periodicals; Computational neuroscience -- Periodicals; 612.80285
• DOI: 10.1155/2015/286354
• Languages: English
• ISSNs: 1687-5265

Abstract

Abstract : The Sudoku problem is a well-known logic-based puzzle of combinatorial number-placement. It consists in filling an 2 × n 2 grid, composed ofn columns, n rows, andn subgrids, each one containing distinct integers from 1 ton 2 . Such a puzzle belongs to the NP-complete collection of problems, to which there exist diverse exact and approximate methods able to solve it. In this paper, we propose a new hybrid algorithm that smartly combines a classic tabu search procedure with thealldifferent global constraint from the constraint programming world. Thealldifferent constraint is known to be efficient for domain filtering in the presence of constraints that must be pairwise different, which are exactly the kind of constraints that Sudokus own. This ability clearly alleviates the work of the tabu search, resulting in a faster and more robust approach for solving Sudokus. We illustrate interesting experimental results where our proposed algorithm outperforms the best results previously reported by hybrids and approximate methods.