TSALSHADE: Improved LSHADE Algorithm with Tangent Search
バージョン 1.0.0 (224 KB) 作成者:
abdesslem layeb
LSHADE algorithm with tangent flight
DE algorithm is among the most successful algorithm for numerical optimization. However, like other metaheuristics, DE suffers from several weaknesses like weak exploration and local minimum stagnation problems. Besides, most DE variants including the most efficient ones like LSHADE variants, suffer in presence of hard composition functions having global optima hard to reach. On the other hand, Tangent Search Algorithm (TSA) has shown an effective ability to deal with hard optimization functions thanks to the tangent flight operator. This one offers an effective way to escape from local optima of hard test functions while preserving good exploration ability. In this scope, a hybrid TSA and LSHADE algorithm called TSALSHADE is proposed. The main advantage of the new proposed algorithm is its ability to deal with hard composite functions. The experimental study on the latest CEC 2022 benchmark functions has shown that TSALSHADE is capable to supply very promising and competitive results on most benchmark functions thanks to a better balance between exploration and exploitation of the search.
引用
abdesslem layeb (2024). TSALSHADE: Improved LSHADE Algorithm with Tangent Search (https://www.mathworks.com/matlabcentral/fileexchange/123400-tsalshade-improved-lshade-algorithm-with-tangent-search), MATLAB Central File Exchange. 取得済み .
MATLAB リリースの互換性
作成:
R2022b
すべてのリリースと互換性あり
プラットフォームの互換性
Windows macOS Linuxタグ
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!バージョン | 公開済み | リリース ノート | |
---|---|---|---|
1.0.0 |