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Application of improved hybrid whale optimization algorithm to optimization problems

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Abstract

The Whale Optimization Algorithm (WOA) is one of the recent meta-heuristic algorithms. WOA has advantages such as an exploration mechanism that leads towards the global optimum, a suitable balance between exploration and exploitation that avoids the local optimum, and a very good exploitation capability. In this study, five new hybrid algorithms are proposed to develop these advantages. Two of them are developed by combining WOA and Particle Swarm Optimization (PSO) algorithms, and three of them are developed by adding the Lévy flight algorithm to this combination in different ways. The proposed algorithms have been tested with 23 mathematical optimization problems, and in order to make a more accurate comparison, the average optimization results and corresponding standard deviation results are calculated by running these algorithms 30 times for each optimization problem. The proposed algorithms' performances were evaluated among themselves, and the WOALFVWPSO algorithm performed better among these algorithms. This proposed algorithm has been first compared with WOA and PSO, then with other algorithms in the literature. According to WOA and PSO, the proposed algorithm performs better in 19 of 23 mathematical optimization problems, and according to other literature, it performs better in 15 of 23 problems. Also, the proposed algorithm has been applied to the pressure vessel design engineering problem and achieved the best result compared to other algorithms in the literature. It has been proven that the WOALFVWPSO algorithm provides competitive solutions for most optimization problems when compared to meta-heuristic algorithms in the literature.

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Acknowledgements

The authors are grateful to the Selcuk University Scientific Research Projects Coordinatorship for support of the manuscript.

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All authors declare that there is no funding for this work.

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Authors and Affiliations

  1. Electronics and Automation, Ilgın Vocational School, Selcuk University, Konya, Turkey

    Mustafa Serter Uzer

  2. Computer Engineering, Faculty of Technology, Selcuk University, Konya, Turkey

    Onur Inan

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  1. Mustafa Serter Uzer
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  2. Onur Inan
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Contributions

MSU and OI conducted the literature review of the manuscript and the design of the proposed method together. It also contributed equally to obtaining the results of the proposed method and interpreting the results. MSU and OI read and approved the final manuscript.

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Correspondence to Mustafa Serter Uzer.

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Uzer, M.S., Inan, O. Application of improved hybrid whale optimization algorithm to optimization problems. Neural Comput & Applic 35, 12433–12451 (2023). https://doi.org/10.1007/s00521-023-08370-x

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