Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models

Abhishake Kundu; Anand Sunder

doi:doi:10.11648/j.ajcst.20210404.15

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Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models

Abhishake Kundu, Anand Sunder

Published in American Journal of Computer Science and Technology (Volume 4, Issue 4)

Received: 18 August 2021 Accepted: 24 November 2021 Published: 2 December 2021

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Abstract

Numerous algorithms for solving sudoku puzzles have been explored, most of which use a backtracking approach. Thus computational efficiency of such algorithms can sometimes yield poor results. We propose a probabilistic solver algorithm which, iteratively fills the sudoku grid and solves the same. In this approach we make use of a dynamic random number set, we identify unassigned sudoku grids for a given puzzle where only one possible value can be filled in and iteratively identify and assign cells with least number of possible values. We not only elaborate on our solver algorithm logic, but also explore application areas based on algorithm devised, after reviewing relevant similar approaches illustrated in the referenced articles. We believe by extension of this algorithm, many combinatorial problems in the field of material characterization, cryptography, cybersecurity can be solved and advanced. We also envision that with application of neural networks, Machine Learning techniques the algorithm will take a very adaptive and robust form, useful for solving complex problems in accurate estimation of missing data, discrete event analysis and prediction. Uniqueness is the ability to use high probability for faster computation and low execution time. With cyberattacks of varied vectors and types, its important to devise a mechanism to create a deliberate mismatch every time a possible attack is detected.

Published in	American Journal of Computer Science and Technology (Volume 4, Issue 4)
DOI	10.11648/j.ajcst.20210404.15
Page(s)	119-128
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Sudoku Solver, Logistic Model, Backtracking, Algorithm

References

[1]	Arnab K Maji, Sudipta Roy and Rajat K Pal (2013). A Novel Algorithmic approach for solving Sudoku puzzle in Guess Free Manner.
[2]	Backtracking approach to Sudoku solver: Geeks for Geeks.
[3]	Exact cover algorithm to solving Sudoku puzzles: Wikipedia.
[4]	Karimi-Dehkordi Z., Zaman far K., Baraani-Dastjerdi A., Ghasem-Aghaee N. (2010) Sudoku Using Parallel Simulated Annealing. In: Tan Y., Shi Y., Tan K. C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6146. Springer, Berlin, Heidelberg.
[5]	John M Weiss. (2009). “Genetic Algorithms and Sudoku”.
[6]	H. L Xao, X. S Ding (2014) “On the Generation and Evaluation of a Sudoku Puzzle”.
[7]	Maria-Ercsey-Ravasz & Zoltan Toroczkai (2012). “The Chaos within Sudoku”.
[8]	Alice H. Becker (2013). “Sudoku and Image Security”.
[9]	Guilio Maier, Vladmir Buljak, Giuseppe Cocheti (2012). “Mechanical Characterization of Materials and Diagnosis of Structures by Inverse Analysis: Some Innovative Procedures and Applications”.
[10]	Lei Gao (2005). “Latin Squares in Experimental Design”.

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APA Style

Abhishake Kundu, Anand Sunder. (2021). Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models. American Journal of Computer Science and Technology, 4(4), 119-128. https://doi.org/10.11648/j.ajcst.20210404.15

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ACS Style

Abhishake Kundu; Anand Sunder. Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models. Am. J. Comput. Sci. Technol. 2021, 4(4), 119-128. doi: 10.11648/j.ajcst.20210404.15

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AMA Style

Abhishake Kundu, Anand Sunder. Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models. Am J Comput Sci Technol. 2021;4(4):119-128. doi: 10.11648/j.ajcst.20210404.15

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@article{10.11648/j.ajcst.20210404.15,
  author = {Abhishake Kundu and Anand Sunder},
  title = {Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models},
  journal = {American Journal of Computer Science and Technology},
  volume = {4},
  number = {4},
  pages = {119-128},
  doi = {10.11648/j.ajcst.20210404.15},
  url = {https://doi.org/10.11648/j.ajcst.20210404.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20210404.15},
  abstract = {Numerous algorithms for solving sudoku puzzles have been explored, most of which use a backtracking approach. Thus computational efficiency of such algorithms can sometimes yield poor results. We propose a probabilistic solver algorithm which, iteratively fills the sudoku grid and solves the same. In this approach we make use of a dynamic random number set, we identify unassigned sudoku grids for a given puzzle where only one possible value can be filled in and iteratively identify and assign cells with least number of possible values. We not only elaborate on our solver algorithm logic, but also explore application areas based on algorithm devised, after reviewing relevant similar approaches illustrated in the referenced articles. We believe by extension of this algorithm, many combinatorial problems in the field of material characterization, cryptography, cybersecurity can be solved and advanced. We also envision that with application of neural networks, Machine Learning techniques the algorithm will take a very adaptive and robust form, useful for solving complex problems in accurate estimation of missing data, discrete event analysis and prediction. Uniqueness is the ability to use high probability for faster computation and low execution time. With cyberattacks of varied vectors and types, its important to devise a mechanism to create a deliberate mismatch every time a possible attack is detected.},
 year = {2021}
}

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TY  - JOUR
T1  - Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models
AU  - Abhishake Kundu
AU  - Anand Sunder
Y1  - 2021/12/02
PY  - 2021
N1  - https://doi.org/10.11648/j.ajcst.20210404.15
DO  - 10.11648/j.ajcst.20210404.15
T2  - American Journal of Computer Science and Technology
JF  - American Journal of Computer Science and Technology
JO  - American Journal of Computer Science and Technology
SP  - 119
EP  - 128
PB  - Science Publishing Group
SN  - 2640-012X
UR  - https://doi.org/10.11648/j.ajcst.20210404.15
AB  - Numerous algorithms for solving sudoku puzzles have been explored, most of which use a backtracking approach. Thus computational efficiency of such algorithms can sometimes yield poor results. We propose a probabilistic solver algorithm which, iteratively fills the sudoku grid and solves the same. In this approach we make use of a dynamic random number set, we identify unassigned sudoku grids for a given puzzle where only one possible value can be filled in and iteratively identify and assign cells with least number of possible values. We not only elaborate on our solver algorithm logic, but also explore application areas based on algorithm devised, after reviewing relevant similar approaches illustrated in the referenced articles. We believe by extension of this algorithm, many combinatorial problems in the field of material characterization, cryptography, cybersecurity can be solved and advanced. We also envision that with application of neural networks, Machine Learning techniques the algorithm will take a very adaptive and robust form, useful for solving complex problems in accurate estimation of missing data, discrete event analysis and prediction. Uniqueness is the ability to use high probability for faster computation and low execution time. With cyberattacks of varied vectors and types, its important to devise a mechanism to create a deliberate mismatch every time a possible attack is detected.
VL  - 4
IS  - 4
ER  -

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Author Information

Abhishake Kundu

Department of Industrial and Manufacturing Systems Engineering, Texas Tech University, Lubbock, USA
Anand Sunder

Capgemini SE, Hyderabad, India

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APA Style

Abhishake Kundu, Anand Sunder. (2021). Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models. American Journal of Computer Science and Technology, 4(4), 119-128. https://doi.org/10.11648/j.ajcst.20210404.15

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ACS Style

Abhishake Kundu; Anand Sunder. Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models. Am. J. Comput. Sci. Technol. 2021, 4(4), 119-128. doi: 10.11648/j.ajcst.20210404.15

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AMA Style

Abhishake Kundu, Anand Sunder. Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models. Am J Comput Sci Technol. 2021;4(4):119-128. doi: 10.11648/j.ajcst.20210404.15

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@article{10.11648/j.ajcst.20210404.15,
  author = {Abhishake Kundu and Anand Sunder},
  title = {Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models},
  journal = {American Journal of Computer Science and Technology},
  volume = {4},
  number = {4},
  pages = {119-128},
  doi = {10.11648/j.ajcst.20210404.15},
  url = {https://doi.org/10.11648/j.ajcst.20210404.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajcst.20210404.15},
  abstract = {Numerous algorithms for solving sudoku puzzles have been explored, most of which use a backtracking approach. Thus computational efficiency of such algorithms can sometimes yield poor results. We propose a probabilistic solver algorithm which, iteratively fills the sudoku grid and solves the same. In this approach we make use of a dynamic random number set, we identify unassigned sudoku grids for a given puzzle where only one possible value can be filled in and iteratively identify and assign cells with least number of possible values. We not only elaborate on our solver algorithm logic, but also explore application areas based on algorithm devised, after reviewing relevant similar approaches illustrated in the referenced articles. We believe by extension of this algorithm, many combinatorial problems in the field of material characterization, cryptography, cybersecurity can be solved and advanced. We also envision that with application of neural networks, Machine Learning techniques the algorithm will take a very adaptive and robust form, useful for solving complex problems in accurate estimation of missing data, discrete event analysis and prediction. Uniqueness is the ability to use high probability for faster computation and low execution time. With cyberattacks of varied vectors and types, its important to devise a mechanism to create a deliberate mismatch every time a possible attack is detected.},
 year = {2021}
}

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TY  - JOUR
T1  - Applications Based on a Novel Sudoku Solver Algorithm and Grid Based Models
AU  - Abhishake Kundu
AU  - Anand Sunder
Y1  - 2021/12/02
PY  - 2021
N1  - https://doi.org/10.11648/j.ajcst.20210404.15
DO  - 10.11648/j.ajcst.20210404.15
T2  - American Journal of Computer Science and Technology
JF  - American Journal of Computer Science and Technology
JO  - American Journal of Computer Science and Technology
SP  - 119
EP  - 128
PB  - Science Publishing Group
SN  - 2640-012X
UR  - https://doi.org/10.11648/j.ajcst.20210404.15
AB  - Numerous algorithms for solving sudoku puzzles have been explored, most of which use a backtracking approach. Thus computational efficiency of such algorithms can sometimes yield poor results. We propose a probabilistic solver algorithm which, iteratively fills the sudoku grid and solves the same. In this approach we make use of a dynamic random number set, we identify unassigned sudoku grids for a given puzzle where only one possible value can be filled in and iteratively identify and assign cells with least number of possible values. We not only elaborate on our solver algorithm logic, but also explore application areas based on algorithm devised, after reviewing relevant similar approaches illustrated in the referenced articles. We believe by extension of this algorithm, many combinatorial problems in the field of material characterization, cryptography, cybersecurity can be solved and advanced. We also envision that with application of neural networks, Machine Learning techniques the algorithm will take a very adaptive and robust form, useful for solving complex problems in accurate estimation of missing data, discrete event analysis and prediction. Uniqueness is the ability to use high probability for faster computation and low execution time. With cyberattacks of varied vectors and types, its important to devise a mechanism to create a deliberate mismatch every time a possible attack is detected.
VL  - 4
IS  - 4
ER  -

Copy | Download