This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Whip Until Solved
January/February 2010 (vol. 12 no. 1)
pp. 73-75

In this installment of Prescriptions, I'll explain how to use iterated projections to design an algorithm for solving Sudoku puzzles. I'll also illustrate why iteration doesn't always give the desired result.

1. T. Yato, and T. Seta, "Complexity and Completeness of Finding another Solution and Its Application to Puzzles," IEICE Trans. Fundamentals Electronics, vol. E86-A, no. 5, 2003, pp. 1052–1060.
2. T.K. Moon, J.H. Gunther, and J. Kupin, "Sinkhorn Solves Sudoku," IEEE Trans. Information Theory, vol. 55, no. 4, 2009, pp. 1741–1746.
3. F. E. Sullivan, "A Generalization of Best Approximation Operators," Annali di Matematica Pura ed Applicata, vol. 107, no. 1, 1975, pp. 245–261.
4. V. Elser, I. Rankenburg, and P. Thibault, "Searching with Iterated Maps," Proc. Nat'l Academy of Sciences, vol. 104, no. 2, 2007, pp. 418–423.

Index Terms:
Computing Prescriptions, Francis Sullivan, Ernst Mucke, Sudoku
Citation:
Francis Sullivan, "Whip Until Solved," Computing in Science and Engineering, vol. 12, no. 1, pp. 73-75, Jan.-Feb. 2010, doi:10.1109/MCSE.2010.19
Usage of this product signifies your acceptance of the Terms of Use.