Solving sudoku puzzles using improved artificial bee colony algorithm

2009 4th International Conference on Innovative Computing, Information and Control, ICICIC 2009

Volumn , Issue , 2009, Pages 885-888

  Pacurib, Jaysonne A ^a   Seno, Glaiza Mae M ^a   Yusiong, John Paul T ^a  

^a UNIVERSITY OF THE PHILIPPINES VISAYAS   (Philippines)

Author keywords

[No Author keywords available]

Indexed keywords

COLONY ALGORITHMS; COMBINATORIAL PROBLEM; COMBINATORIAL PUZZLES; HARD PROBLEMS; NP COMPLETE PROBLEMS;

ALGORITHMS; COMPUTATIONAL COMPLEXITY;

COMBINATORIAL MATHEMATICS;

EID: 77951492454     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICICIC.2009.334     Document Type: Conference Paper

References (12)

1. Basturk, B. and Karaboga, D., An Artificial Bee Colony (ABC) Algorithm for Numeric Function Optimization. IEEE Swarm Intelligence Symposium 2006, vol.8, Issue 1, 2006, pp. 687-697.
2. Baykasoglu, A., Ozbakor, L., and Tapkan, P., Artificial Bee Colony Algorithm and Its Application to Generalized Assignment Problem, I-Tech Education and Publishing, Vienna, Austria, 2007, pp. 113-144.
3. Chong, C. S., Low M. Y. H., Sivakumar, A. I., and Gay, K. L., A Bee Colony Optimization Algorithm to Job Shop Scheduling, Proceedings of the 37th Winter Simulation Conference, 2006, pp. 1954-1961.
4. Crawford, B., Aranda, M., Castro, C., and Monfroy, E., Using Constraint Programming to solve Sudoku Puzzles. ICCIT Proceedings of the 2008 Third International Conference on Convergence and Hybrid Information Technology, Vol.2, 2008, pp. 926-931.
5. Karaboga, D., An Idea Based on Honey Bee Swarm for Numerical Optimization, Technical Report-TR06, Erciyes University, Engineering Faculty, Computer Engineering Department, Turkey, October, 2005.
6. Lewis, R., Metaheuristics can Solve Sudoku Puzzles, Journal of Heuristics, vol.13, no.4, 2007, pp. 387-401. (Pubitemid 47117882)
7. Mantere, T. and Koljonen, J., Solving and rating Sudoku puzzles with Genetic Algorithms, IEEE Congress on Evolutionary Computation, 2007, pp. 1382-1389.
8. Moon, T. K., and Gunther, J. H., Multiple Constraint Satisfaction by Belief Propagation: An Example of Using Sudoku, IEEE Mountain Workshop on Adaptive and Learning Systems, 2006, pp. 122-126.
9. Mullaney, D., Using Ant Systems to Solve Sudoku Problems, Springer Publishing Company, 2006.
10. Perez, M. and Marwala, T., Stochastic Optimization Approaches for Solving Sudoku, arXiv:0805.0697v1, 2008.
11. Quan, H., and Shi, X., On the Analysis of Performance of the Improved Artificial-Bee-Colony Algorithm, Proceedings of the 2008 Fourth International Conference on Natural Computation, vol.7, 2007, pp. 654-658.
12. Yato, T. and Seta, T., Complexity and Completeness of Finding Another Solution and Its Application to Puzzles, IEICE Trans. Fundamentals, vol.E86-A, no.5, 2003, pp. 1052-1060.