Geometric particle swarm optimization for the sudoku puzzle
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Solving Sudoku Puzzles with Rewriting Rules
Electronic Notes in Theoretical Computer Science (ENTCS)
Metaheuristics can solve sudoku puzzles
Journal of Heuristics
Using Constraint Programming to solve Sudoku Puzzles
ICCIT '08 Proceedings of the 2008 Third International Conference on Convergence and Hybrid Information Technology - Volume 02
IJCAI'77 Proceedings of the 5th international joint conference on Artificial intelligence - Volume 2
IEEE Transactions on Information Theory
Entropy Minimization for Solving Sudoku
IEEE Transactions on Signal Processing
Parameter tuning of a choice-function based hyperheuristic using Particle Swarm Optimization
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
The Sudoku problem consists in filling a n^2xn^2 grid so that each column, row and each one of the nxn sub-grids contain different digits from 1 to n^2. This is a non-trivial problem, known to be NP-complete. The literature reports different incomplete search methods devoted to tackle this problem, genetic computing being the one exhibiting the best results. In this paper, we propose a new hybrid AC3-tabu search algorithm for Sudoku problems. We merge a classic tabu search procedure with an arc-consistency 3 (AC3) algorithm in order to effectively reduce the combinatorial space. The role of AC3 here is do not only acting as a single pre-processing phase, but as a fully integrated procedure that applies at every iteration of the tabu search. This integration leads to a more effective domain filtering and therefore to a faster resolution process. We illustrate experimental evaluations where our approach outperforms the best results reported by using incomplete search methods.