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Golden Sine Algorithm: A Novel Math-Inspired AlgorithmTANYILDIZI, E. , DEMIR, G.
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artificial intelligence, computational intelligence, evolutionary computation, heuristic algorithms, optimization
optimization(24), algorithm(14), algorithms(7), inspired(5), computation(5), yang(4), swarm(4), software(4), jadvengsoft(4), evolutionary(4)
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About this article
Date of Publication: 2017-05-31
Volume 17, Issue 2, Year 2017, On page(s): 71 - 78
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2017.02010
Web of Science Accession Number: 000405378100010
SCOPUS ID: 85020089767
In this study, Golden Sine Algorithm (Gold-SA) is presented as a new metaheuristic method for solving optimization problems. Gold-SA has been developed as a new search algorithm based on population. This math-based algorithm is inspired by sine that is a trigonometric function. In the algorithm, random individuals are created as many as the number of search agents with uniform distribution for each dimension. The Gold-SA operator searches to achieve a better solution in each iteration by trying to bring the current situation closer to the target value. The solution space is narrowed by the golden section so that the areas that are supposed to give only good results are scanned instead of the whole solution space scan. In the tests performed, it is seen that Gold-SA has better results than other population based methods. In addition, Gold-SA has fewer algorithm-dependent parameters and operators than other metaheuristic methods, increasing the importance of this method by providing faster convergence of this new method.
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