Research Article
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Year 2025, Volume: 38 Issue: 4, 1754 - 1768, 01.12.2025
https://doi.org/10.35378/gujs.1406713

Abstract

References

  • [1] Colbourn, C. J., “The complexity of completing partial latin squares”, Discret. Appl. Math., 8 (1): 25-30, (1984). DOI: https://doi.org/10.1016/0166-218X(84)90075-1
  • [2] Garey, J. D., M. R., “Computers and intractability”, A Guide to the Theory of Np-completeness. 338: 79-80, (1979). DOI: https://doi.org/10.1137/1024022
  • [3] Andersson, D., “Hashiwokakero is NP-complete’’, Inf. Processing Letters 109(19): 1145-1146, (2009). DOI: 10.1016/j.ipl.2009.07.017
  • [4] Kölker, J., “Kurodokora is NP-complete”, J. of Inf. Processing 20(3): 694-706, (2012). DOI: 10.1177/1073858411435128
  • [5] Haraguchi, K., Ono, H., “Approximability of latin square completion-type puzzles,” in Fun with Algorithms - 7th International Conference, FUN 2014, Lipari Island, Sicily, Italy, July 1-3, 2014. Proceedings, 8496, (2014). DOI: 10.1007/978-3-319-07890-8_19
  • [6] Donovan, D. M., “The completion of partial latin squares”, Australas. J Comb., 22:247-264, (2000).
  • [7] Norvig, P., “Solving every sudoku puzzle,” http://norvig.com/sudoku.html, (2018).
  • [8] Dorigo, M., Birattari, M., Stützle, T., “Ant colony optimization,” IEEE Comput. Intell. Mag., 1(4):28-39, (2006). DOI: 10.1109/MCI.2006.329691
  • [9] Solnon, C., Khichane M., Albert P., “Strong combination of ant colony optimization with constraint programming optimization,” Integration of AI and or Techniques in Constraint Programming for Combinatorial Optimization Problems, 7th International Conference, CPAIOR 2010, Bologna, Italy, June 14-18, (2010). DOI: 10.1007/978-3-642-13520-26
  • [10] Lloyd, H., Amos, M., “Solving sudoku with ant colony optimization,” IEEE Trans. Games, 12(3):302-311, (2020). DOI: https://doi.org/10.1109/tg.2019.2942773
  • [11] Knuth, D. E., Davies, J., Roscoe, B., Woodcock, J., “Millennial perspectives in computerscience,” Proceedings of the 1999 Oxford-Microsoft Symposium, 187-214, (2000). DOI: 10.1145/2576802.2576832
  • [12] Şen, B. B., Diner, Ö. Y., “List coloring based algorithm for the Futoshiki puzzle,” An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 14(4): 294–307, (2024). DOI: 10.11121/ijocta.1432
  • [13] Bishop, J. M., “Stochastic Searching Networks”, IEE Conf. Artificial Neural Networks, 329-331, (1989). 10.1007/978-94-011-2360-0_24
  • [14] Lastrina, M. A., “List-coloring and sum-list-coloring problems on graphs”, Graduate thesis and dissertations, Iawo University, (2012).
  • [15] Tuza, Z., “Graph colorings with local restrictions - a survey,” Discussiones Mathematicae Graph Theory, 17: 161-228, (1997). DOI: doi.org/10.7151/dmgt.1049
  • [16] Vizing, V., “Coloring the vertices of a graph in prescribed colors,” Metody Diskret. Anal. v. Teorii Kodov i Shem, 101(29):3-10, (1976).
  • [17] Beni, G., Wang, J., ‘‘Swarm intelligence in cellular robotic systems’’, Robots and Biological Systems: Towards a New Bionics, 102: 703-712, (1993). DOI: 10.1007/978-3-642-58069-7_38
  • [18] Kennedy, J., Eberhart, R., “Particle swarm optimization”, Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, 1942-1948, (1995). DOI: http://dx.doi.org/10.1109/ICNN.1995.488968
  • [19] Musliu, N., Winter, F., “A hybrid approach for the sudoku problem: Using constraint programming in iterated local search,” IEEE Intell. Syst., 32(2):52-62, (2017). DOI: 10.1109/MIS.2017.29
  • [20] Amos, M., Crossley, M., Llyod H., “Solving nurikabe with ant colony optimization,” the Genetic and Evolutionary Computation Conference Companion, 129-130, (2019). DOI: https://doi.org/10.1145/3319619.3338470 [21] Pillay, N., “Finding solutions to sudoku puzzles using human intuitive heuristics,” South Afr. Comput. J., 49:25-34, (2012).
  • [22] Li, S., Wei, Y., Liu, X., Zhu, H., Yu, Z., “A New Fast Ant Colony Optimization Algorithm: The Saltatory Evolution Ant Colony Optimization Algorithm.” Mathematics, 10, 925, (2022). DOI: 10.3390/math10060925
  • [23] Wang, C., Sun, B., Du, K.J., Li, J.Y., Zhan, Z.H., Jeon, S.W., Wang, H., Zhang, J., “A novel evolutionary algorithm with column and sub-block local search for sudoku puzzles”, IEEE Transactions on Game, 1-11, (2023). DOI: 10.1109/TG.2023.3236490

Ant Colony Optimization Algorithm for the Futoshiki Puzzle

Year 2025, Volume: 38 Issue: 4, 1754 - 1768, 01.12.2025
https://doi.org/10.35378/gujs.1406713

Abstract

Futoshiki is a computationally hard problem belonging to the Latin Square Completion-type Puzzles. It is played on a partially filled n×n grid that may include inequality constraints between cells. The objective is to complete the grid such that each row and column contains the integers from 1 to n exactly once, while also satisfying all inequality constraints. In this work, we propose FutoshikiACO, an Ant Colony Optimization-based algorithm to solve Futoshiki instances of fixed size. We evaluate the performance of this stochastic method through computational experiments. Compared to existing deterministic approaches, FutoshikiACO explores a significantly reduced search space. Our results not only demonstrate the inherent complexity of the Futoshiki problem but also highlight the types of instances where ant colony-based metaheuristics are particularly effective in solving such constraint satisfaction problems.

References

  • [1] Colbourn, C. J., “The complexity of completing partial latin squares”, Discret. Appl. Math., 8 (1): 25-30, (1984). DOI: https://doi.org/10.1016/0166-218X(84)90075-1
  • [2] Garey, J. D., M. R., “Computers and intractability”, A Guide to the Theory of Np-completeness. 338: 79-80, (1979). DOI: https://doi.org/10.1137/1024022
  • [3] Andersson, D., “Hashiwokakero is NP-complete’’, Inf. Processing Letters 109(19): 1145-1146, (2009). DOI: 10.1016/j.ipl.2009.07.017
  • [4] Kölker, J., “Kurodokora is NP-complete”, J. of Inf. Processing 20(3): 694-706, (2012). DOI: 10.1177/1073858411435128
  • [5] Haraguchi, K., Ono, H., “Approximability of latin square completion-type puzzles,” in Fun with Algorithms - 7th International Conference, FUN 2014, Lipari Island, Sicily, Italy, July 1-3, 2014. Proceedings, 8496, (2014). DOI: 10.1007/978-3-319-07890-8_19
  • [6] Donovan, D. M., “The completion of partial latin squares”, Australas. J Comb., 22:247-264, (2000).
  • [7] Norvig, P., “Solving every sudoku puzzle,” http://norvig.com/sudoku.html, (2018).
  • [8] Dorigo, M., Birattari, M., Stützle, T., “Ant colony optimization,” IEEE Comput. Intell. Mag., 1(4):28-39, (2006). DOI: 10.1109/MCI.2006.329691
  • [9] Solnon, C., Khichane M., Albert P., “Strong combination of ant colony optimization with constraint programming optimization,” Integration of AI and or Techniques in Constraint Programming for Combinatorial Optimization Problems, 7th International Conference, CPAIOR 2010, Bologna, Italy, June 14-18, (2010). DOI: 10.1007/978-3-642-13520-26
  • [10] Lloyd, H., Amos, M., “Solving sudoku with ant colony optimization,” IEEE Trans. Games, 12(3):302-311, (2020). DOI: https://doi.org/10.1109/tg.2019.2942773
  • [11] Knuth, D. E., Davies, J., Roscoe, B., Woodcock, J., “Millennial perspectives in computerscience,” Proceedings of the 1999 Oxford-Microsoft Symposium, 187-214, (2000). DOI: 10.1145/2576802.2576832
  • [12] Şen, B. B., Diner, Ö. Y., “List coloring based algorithm for the Futoshiki puzzle,” An International Journal of Optimization and Control: Theories & Applications (IJOCTA), 14(4): 294–307, (2024). DOI: 10.11121/ijocta.1432
  • [13] Bishop, J. M., “Stochastic Searching Networks”, IEE Conf. Artificial Neural Networks, 329-331, (1989). 10.1007/978-94-011-2360-0_24
  • [14] Lastrina, M. A., “List-coloring and sum-list-coloring problems on graphs”, Graduate thesis and dissertations, Iawo University, (2012).
  • [15] Tuza, Z., “Graph colorings with local restrictions - a survey,” Discussiones Mathematicae Graph Theory, 17: 161-228, (1997). DOI: doi.org/10.7151/dmgt.1049
  • [16] Vizing, V., “Coloring the vertices of a graph in prescribed colors,” Metody Diskret. Anal. v. Teorii Kodov i Shem, 101(29):3-10, (1976).
  • [17] Beni, G., Wang, J., ‘‘Swarm intelligence in cellular robotic systems’’, Robots and Biological Systems: Towards a New Bionics, 102: 703-712, (1993). DOI: 10.1007/978-3-642-58069-7_38
  • [18] Kennedy, J., Eberhart, R., “Particle swarm optimization”, Proceedings of International Conference on Neural Networks (ICNN'95), Perth, WA, Australia, 1942-1948, (1995). DOI: http://dx.doi.org/10.1109/ICNN.1995.488968
  • [19] Musliu, N., Winter, F., “A hybrid approach for the sudoku problem: Using constraint programming in iterated local search,” IEEE Intell. Syst., 32(2):52-62, (2017). DOI: 10.1109/MIS.2017.29
  • [20] Amos, M., Crossley, M., Llyod H., “Solving nurikabe with ant colony optimization,” the Genetic and Evolutionary Computation Conference Companion, 129-130, (2019). DOI: https://doi.org/10.1145/3319619.3338470 [21] Pillay, N., “Finding solutions to sudoku puzzles using human intuitive heuristics,” South Afr. Comput. J., 49:25-34, (2012).
  • [22] Li, S., Wei, Y., Liu, X., Zhu, H., Yu, Z., “A New Fast Ant Colony Optimization Algorithm: The Saltatory Evolution Ant Colony Optimization Algorithm.” Mathematics, 10, 925, (2022). DOI: 10.3390/math10060925
  • [23] Wang, C., Sun, B., Du, K.J., Li, J.Y., Zhan, Z.H., Jeon, S.W., Wang, H., Zhang, J., “A novel evolutionary algorithm with column and sub-block local search for sudoku puzzles”, IEEE Transactions on Game, 1-11, (2023). DOI: 10.1109/TG.2023.3236490
There are 22 citations in total.

Details

Primary Language English
Subjects Algorithms and Calculation Theory
Journal Section Research Article
Authors

Banu Baklan Sen 0000-0003-4545-5044

Öznur Yaşar 0000-0002-9271-2691

Early Pub Date November 15, 2025
Publication Date December 1, 2025
Submission Date December 19, 2023
Acceptance Date September 29, 2025
Published in Issue Year 2025 Volume: 38 Issue: 4

Cite

APA Baklan Sen, B., & Yaşar, Ö. (2025). Ant Colony Optimization Algorithm for the Futoshiki Puzzle. Gazi University Journal of Science, 38(4), 1754-1768. https://doi.org/10.35378/gujs.1406713
AMA Baklan Sen B, Yaşar Ö. Ant Colony Optimization Algorithm for the Futoshiki Puzzle. Gazi University Journal of Science. December 2025;38(4):1754-1768. doi:10.35378/gujs.1406713
Chicago Baklan Sen, Banu, and Öznur Yaşar. “Ant Colony Optimization Algorithm for the Futoshiki Puzzle”. Gazi University Journal of Science 38, no. 4 (December 2025): 1754-68. https://doi.org/10.35378/gujs.1406713.
EndNote Baklan Sen B, Yaşar Ö (December 1, 2025) Ant Colony Optimization Algorithm for the Futoshiki Puzzle. Gazi University Journal of Science 38 4 1754–1768.
IEEE B. Baklan Sen and Ö. Yaşar, “Ant Colony Optimization Algorithm for the Futoshiki Puzzle”, Gazi University Journal of Science, vol. 38, no. 4, pp. 1754–1768, 2025, doi: 10.35378/gujs.1406713.
ISNAD Baklan Sen, Banu - Yaşar, Öznur. “Ant Colony Optimization Algorithm for the Futoshiki Puzzle”. Gazi University Journal of Science 38/4 (December2025), 1754-1768. https://doi.org/10.35378/gujs.1406713.
JAMA Baklan Sen B, Yaşar Ö. Ant Colony Optimization Algorithm for the Futoshiki Puzzle. Gazi University Journal of Science. 2025;38:1754–1768.
MLA Baklan Sen, Banu and Öznur Yaşar. “Ant Colony Optimization Algorithm for the Futoshiki Puzzle”. Gazi University Journal of Science, vol. 38, no. 4, 2025, pp. 1754-68, doi:10.35378/gujs.1406713.
Vancouver Baklan Sen B, Yaşar Ö. Ant Colony Optimization Algorithm for the Futoshiki Puzzle. Gazi University Journal of Science. 2025;38(4):1754-68.