Tangent Search Algorithm for Solving Optimization Problem

版本 1.0.5 (12.1 KB) 作者: abdesslem layeb
This code implements a new population-based optimization algorithm called the Tangent Search Algorithm (TSA) and a light version sTSA
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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

引用格式

abdesslem layeb (2025). Tangent Search Algorithm for Solving Optimization Problem (https://ww2.mathworks.cn/matlabcentral/fileexchange/89897-tangent-search-algorithm-for-solving-optimization-problem), MATLAB Central File Exchange. 检索时间: .

Layeb, Abdesslem. "Tangent search algorithm for solving optimization problems." Neural Computing and Applications (2022): 1-32.

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版本 已发布 发行说明
1.0.5

update sTSA
1.0.4

A simple tangent search algorithm with large and small tangent flight (sTSA)
1.0.3

code improved
1.0.2

code improved
1.0.1

test functions added
1.0.0