Abstract
Simulated Annealing is one of the leading stochastic optimization algorithms. Parallel Simulated annealing, as a modification of Simulated annealing, if properly adapted, is able to solve the problem of selected global optimization issues. An example of a linearly dependent representative of problems in which we are looking for just one solution or global optimum is publicly known as a Sudoku puzzle. The object of this project is to study behaviour of Simulated annealing and Parallel simulated annealing by finding solutions to the Sudoku puzzle, evaluate and verify the success and efficiency of these algorithms, compared to the Backtracking algorithm.
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Clementis, L. (2015). Advantage of Parallel Simulated Annealing Optimization by Solving Sudoku Puzzle. In: Sinčák, P., Hartono, P., Virčíková, M., Vaščák, J., Jakša, R. (eds) Emergent Trends in Robotics and Intelligent Systems. Advances in Intelligent Systems and Computing, vol 316. Springer, Cham. https://doi.org/10.1007/978-3-319-10783-7_23
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DOI: https://doi.org/10.1007/978-3-319-10783-7_23
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10782-0
Online ISBN: 978-3-319-10783-7
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