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A novel generalized normal distribution arithmetic optimization algorithm for global optimization and data clustering problems

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Abstract

In the recent years of the progress of data volumes and the emergence of complexity in solving large and complex problems, the need for advanced and intelligent methods to deal with these problems has become a necessity. In this paper, we devised an innovative method using a set of elements of intelligent optimization algorithms to solve a set of problems requiring advanced methods to deal with them. In the proposed method, which is called GNDAOA, three main components are used: Arithmetic Optimization Algorithm (AOA), Generalized Normal Distribution Optimization (GNF), and Opposition-based Learning strategy (OBL). These components are used based on a novel transition mechanism to arrange the executions of the used methods during the optimization process to tackle the main weaknesses of the original methods. Two main problems are used to validate the performance of the proposed method; 23 benchmark functions and 8 data clustering problems. The results of the proposed method are compared with several other well-established methods. The proposed GNDAOA method got the best results in 93% of the tested cases of the benchmark functions. It performed very well by a promising behavior to deal with data clustering applications and gained more than 90% improvements compared to the original methods.

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Acknowledgements

This study was financially supported via a funding grant by Deanship of Scientific Research, Taif University Researchers Supporting Project number (TURSP-2020/300), Taif University, Taif, Saudi Arabia

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Authors and Affiliations

  1. Faculty of Computer Sciences and Informatics, Amman Arab University, 11953, Amman, Jordan

    Laith Abualigah

  2. School of Computer Sciences, Universiti Sains Malaysia, Pulau Pinang, 11800, Malaysia

    Laith Abualigah

  3. Department of Management Information System, College of Business Administration, Taif University, P.O. BOX 11099, Taif, 21944, Saudi Arabia

    Maryam Altalhi

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  1. Laith Abualigah
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Correspondence to Laith Abualigah.

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Abualigah, L., Altalhi, M. A novel generalized normal distribution arithmetic optimization algorithm for global optimization and data clustering problems. J Ambient Intell Human Comput 15, 389–417 (2024). https://doi.org/10.1007/s12652-022-03898-7

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