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INFO: Efficient Optimizer based on Weighted Mean of Vectors

version 1.0.2 (7.51 KB) by Ali Asghar Heidari
INFO: An Efficient Optimization Algorithm based on Weighted Mean of Vectors The source codes at: https://aliasgharheidari.com/INFO.html

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Updated 03 Feb 2022

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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.

Cite As

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.

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MATLAB Release Compatibility
Created with R2021b
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