Work In Progress Solving Sudoku Puzzles Using Hybrid Ant Colony Optimization Algorithm
Yazarlar (1)
Doç. Dr. İbrahim SABUNCU Yalova Üniversitesi, Türkiye
| Bildiri Türü |
Tebliğ/Bildiri
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Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| DOI Numarası | 10.4108/icst.iniscom.2015.258984 | ||
| Kongre Adı | Proceedings of the 1st International Conference on Industrial Networks and Intelligent Systems | ||
| Kongre Tarihi | 02-03-2015 / 04-03-2015 | ||
| Basıldığı Ülke | Japonya | Basıldığı Şehir | Tokyo, Japan |
| Bildiri Linki | https://eudl.eu/doi/10.4108/icst.iniscom.2015.258984 | ||
| Özet |
| Sudoku puzzle is a popular logic game since 2005. This puzzle is an NP-Complete problem which means that a very hard problem that is required deep and efficient algorithm to be solved. So it also draws attention of the scientists to develop methods and algorithm in order to solve Sudoku puzzles. In this study I tried to develop a hybrid algorithm which consist both analytical and heuristic steps to solve the Sudoku puzzle. The developed hybrid algorithm includes two analytical steps and one heuristically step. In the first analytical step, basic manual Sudoku solving methods are used to solve the puzzle. If puzzle is not solved completely than improvement analytical step is applied to solve the puzzle. If still puzzle is not solved completely then heuristic step applied to solve the puzzle completely. In the heuristic step ant colony optimization algorithm (ACO) will be applied to the puzzle. Experiments show that this hybrid ACO algorithm can solve the hardest Sudoku puzzles less than one second. As a result, this study shows that ACO is an effective method that can be applied to solve Sudoku puzzles. |
| Anahtar Kelimeler |
| Ant Colony Optimization | Hybrid Algorithm | Sudoku |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları |