INFO: Efficient Optimizer based on Weighted Mean of Vectors
Version 1.0.4 (3,14 Mo) par
Ali Asghar Heidari
INFO: An Efficient Optimization Algorithm based on Weighted Mean of Vectors The source codes at: https://aliasgharheidari.com/INFO.html
The source codes of this algorithm are publicly available at https://aliasgharheidari.com/INFO.html. This study presents the analysis and principle of an innovative optimizer named weIghted meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean method, whereby the weighted mean idea is employed for a solid structure and updating the vectors’ position using three core procedures: updating rule, vector combining, and a local search. The updating rule stage is based on a mean-based law and convergence acceleration to generate new vectors. The vector combining stage creates a combination of obtained vectors with the updating rule to achieve a promising solution. The updating rule and vector combining steps were improved in INFO to increase the exploration and exploitation capacities. Moreover, the local search stage helps this algorithm escape low-accuracy solutions and improve exploitation and convergence. The performance of INFO was evaluated in 48 mathematical test functions, and five constrained engineering test cases. According to the literature, the results demonstrate that INFO outperforms other basic and advanced methods in terms of exploration and exploitation. In the case of engineering problems, the results indicate that the INFO can converge to 0.99% of the global optimum solution. Hence, the INFO algorithm is a promising tool for optimal designs in optimization problems, which stems from the considerable efficiency of this algorithm for optimizing constrained cases. The source codes of this algorithm will be publicly available at https://imanahmadianfar.com. and https://aliasgharheidari.com/INFO.html.
Citation pour cette source
Ahmadianfar, Iman, et al. “INFO: An Efficient Optimization Algorithm Based on Weighted Mean of Vectors.” Expert Systems with Applications, Elsevier BV, Jan. 2022, p. 116516, doi:10.1016/j.eswa.2022.116516.
Compatibilité avec les versions de MATLAB
Créé avec
R2021b
Compatible avec toutes les versions
Plateformes compatibles
Windows macOS LinuxTags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Découvrir Live Editor
Créez des scripts avec du code, des résultats et du texte formaté dans un même document exécutable.
Artemisinin Optimizer (AO)-2024
Educational Competition Optimizer (ECO)-2024
Fata Morgana Algorithm (FATA)-2024
Harris Hawk Optimization (HHO)-2019
Hunger Games Search (HGS)-2021
Moss Growth Optimization (MGO)-2024
Parrot Optimizer (PO)-2024
Polar Lights Optimizer (PLO)-2024
Rime Optimization Algorithm (RIME)-2023/RIME Iteration version
Rime Optimization Algorithm (RIME)-2023/RIME function evaluation version
Runge Kutta Optimization (RUN)-2021
Slime mould algorithm (SMA)-2020
Weighted Mean of Vectors (INFO)-2022
Version | Publié le | Notes de version | |
---|---|---|---|
1.0.4 | 2024 |
||
1.0.3 | . |
||
1.0.2 | enhance in few lines |
||
1.0.1 | cover added |
||
1.0.0 |