There are many approaches proposed for solving
Sudoku puzzles. One of them is by modelling the puzzles as block
world problems. There have been three model for Sudoku solvers
based on this approach. Each model expresses Sudoku solver as
a parameterized multi agent systems. In this work, we propose a
new model which is an improvement over the existing models. This
paper presents the development of a Sudoku solver that implements
all the proposed models. Some experiments have been conducted to
determine the performance of each model.
[1] A. Bartlett, et.al. An Integer Programming Model for the Sudoku
Problem, The Journal of Online Mathematics and Its Applications:
Volume 8, Issue May, 2008.
[2] X.Q. Deng & Y.D. Li A novel hybrid genetic algorithm for solving
Sudoku puzzle., Optimization Letters, February 2013, Volume 7, Issue
2, pp 241-257, Springer.
[3] Wayne Gould. Su Doku Junior. Penerbit Erlangga. 2005.
[4] R. Lewis, Metaheuristics can solve Sudoku puzzles, Journal of Heuristics,
Vol. 13, 2007, pp. 387-401.
[5] I. Lynce & J. Ouaknine. Sudoku as a SAT problem, Proc. of the 9th
Symposium on Artificial Intelligence and Mathematics, 2006.
[6] T. Mantere. Solving, rating and generating Sudoku puzzles with GA.,
Proc. of IEEE Congress on of Evolutionary Computation, 2007. CEC
2007, Singapore.
[7] P. Malakonakis, et.al. An FPGA-based Sudoku Solver based on Simulated
Annealing methods., Proc. of International Conference on Field-
Programmable Technology, 2009. FPT 2009.
[8] V. Mladenov, et.al., Solving Sudoku Puzzles by using Hopfield Neural
Networks, Proc. of ICACM’11 Proceedings of the 2011 international
conference on Applied & computational mathematics, pp.174-179 World
Scientific and Engineering Academy and Society (WSEAS) Stevens
Point, Wisconsin, USA, 2011.
[9] J. Monk, et.al. Solving Sudoku using Particle Swarm Optimization on
CUDA, Proc. of The 2012 International Conference on Parallel and
Distributed Processing Techniques and Applications, 2012,.
[10] A. Moraglio & J. Togelius, Geometric Particle Swarm Optimization for
the Sudoku Puzzle, Proc. of Conference in Genetic and Evolutionary
Computation, GECCO 2007, Proceedings, London, England, UK, July
7-11, 2007. ACM 2007.
[11] C.E. Nugraheni & L. Abednego. Modelling Sudokus as Block World
Problems. International Journal of Computer, Information, Systems and
Control Engineering, volume 7, no. 8, pp. 48-54, World Academy of
Science, Engineering and Technology, 2013.
[12] Thomas Ag. S. Sudoku - Edisi Lengkap dengan 270 Aneka Teka-teki
Sudoku. Penerbit Andi. 2012.
[13] T.-W. Yue & Z.-C. Lee, Sudoku Solver by Q´tron Neural Networks, Proc.
of International Conference in Intelligent Computing 2006, ICIC2006,
LNCS 4113, pp.943-952, 2006, Springer-Verlag, Berlin Heidelberg
2006.
[1] A. Bartlett, et.al. An Integer Programming Model for the Sudoku
Problem, The Journal of Online Mathematics and Its Applications:
Volume 8, Issue May, 2008.
[2] X.Q. Deng & Y.D. Li A novel hybrid genetic algorithm for solving
Sudoku puzzle., Optimization Letters, February 2013, Volume 7, Issue
2, pp 241-257, Springer.
[3] Wayne Gould. Su Doku Junior. Penerbit Erlangga. 2005.
[4] R. Lewis, Metaheuristics can solve Sudoku puzzles, Journal of Heuristics,
Vol. 13, 2007, pp. 387-401.
[5] I. Lynce & J. Ouaknine. Sudoku as a SAT problem, Proc. of the 9th
Symposium on Artificial Intelligence and Mathematics, 2006.
[6] T. Mantere. Solving, rating and generating Sudoku puzzles with GA.,
Proc. of IEEE Congress on of Evolutionary Computation, 2007. CEC
2007, Singapore.
[7] P. Malakonakis, et.al. An FPGA-based Sudoku Solver based on Simulated
Annealing methods., Proc. of International Conference on Field-
Programmable Technology, 2009. FPT 2009.
[8] V. Mladenov, et.al., Solving Sudoku Puzzles by using Hopfield Neural
Networks, Proc. of ICACM’11 Proceedings of the 2011 international
conference on Applied & computational mathematics, pp.174-179 World
Scientific and Engineering Academy and Society (WSEAS) Stevens
Point, Wisconsin, USA, 2011.
[9] J. Monk, et.al. Solving Sudoku using Particle Swarm Optimization on
CUDA, Proc. of The 2012 International Conference on Parallel and
Distributed Processing Techniques and Applications, 2012,.
[10] A. Moraglio & J. Togelius, Geometric Particle Swarm Optimization for
the Sudoku Puzzle, Proc. of Conference in Genetic and Evolutionary
Computation, GECCO 2007, Proceedings, London, England, UK, July
7-11, 2007. ACM 2007.
[11] C.E. Nugraheni & L. Abednego. Modelling Sudokus as Block World
Problems. International Journal of Computer, Information, Systems and
Control Engineering, volume 7, no. 8, pp. 48-54, World Academy of
Science, Engineering and Technology, 2013.
[12] Thomas Ag. S. Sudoku - Edisi Lengkap dengan 270 Aneka Teka-teki
Sudoku. Penerbit Andi. 2012.
[13] T.-W. Yue & Z.-C. Lee, Sudoku Solver by Q´tron Neural Networks, Proc.
of International Conference in Intelligent Computing 2006, ICIC2006,
LNCS 4113, pp.943-952, 2006, Springer-Verlag, Berlin Heidelberg
2006.
@article{"International Journal of Information, Control and Computer Sciences:56745", author = "Luciana Abednego and Cecilia Nugraheni", title = "A Block World Problem Based Sudoku Solver", abstract = "There are many approaches proposed for solving
Sudoku puzzles. One of them is by modelling the puzzles as block
world problems. There have been three model for Sudoku solvers
based on this approach. Each model expresses Sudoku solver as
a parameterized multi agent systems. In this work, we propose a
new model which is an improvement over the existing models. This
paper presents the development of a Sudoku solver that implements
all the proposed models. Some experiments have been conducted to
determine the performance of each model.
", keywords = "Sudoku puzzle, Sudoku solver, block world problem,
parameterized multi agent systems.", volume = "8", number = "8", pages = "1334-5", }
