Tangent Search Algorithm for Solving Optimization Problem
버전 1.0.5 (12.1 KB) 작성자:
abdesslem layeb
This code implements a new population-based optimization algorithm called the Tangent Search Algorithm (TSA) and a light version sTSA
This code implements a new population-based optimization algorithm called the Tangent Search Algorithm (TSA) to solve optimization problems. The TSA uses a mathematical model based on the tangent function to move a given solution toward a better solution. The tangent flight function has the advantage to balance between the exploitation and the exploration search. Moreover, a novel escape procedure is used to avoid to be trapped in local minima. Besides, an adaptive variable step size is also integrated in this algorithm to enhance the convergence capacity.
TSA: the original code of the paper" Layeb, Abdesslem. "Tangent search algorithm for solving optimization problems." Neural Computing and Applications (2022): 1-32."
sTSA: light and efficient version of TSA
인용 양식
abdesslem layeb (2024). Tangent Search Algorithm for Solving Optimization Problem (https://www.mathworks.com/matlabcentral/fileexchange/89897-tangent-search-algorithm-for-solving-optimization-problem), MATLAB Central File Exchange. 검색됨 .
Layeb, Abdesslem. "Tangent search algorithm for solving optimization problems." Neural Computing and Applications (2022): 1-32.
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R2021a
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Start Hunting!버전 | 게시됨 | 릴리스 정보 | |
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1.0.5 | update sTSA |
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1.0.4 | A simple tangent search algorithm with large and small tangent flight (sTSA) |
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1.0.3 | code improved |
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1.0.2 | code improved |
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1.0.1 | test functions added |
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1.0.0 |
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