Flower pollination algorithm parameters tuning

Mergos, Panagiotis E. ORCID logoORCID: https://orcid.org/0000-0003-3817-9520 and Yang, Xin-She ORCID logoORCID: https://orcid.org/0000-0001-8231-5556 (2021) Flower pollination algorithm parameters tuning. Soft Computing, 25 (22) . pp. 14429-14447. ISSN 1432-7643 [Article] (doi:10.1007/s00500-021-06230-1)

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The flower pollination algorithm (FPA) is a highly efficient metaheuristic optimization algorithm that is inspired by the pollination process of flowering species. FPA is characterised by simplicity in its formulation and high computational performance. Previous studies on FPA assume fixed parameter values based on empirical observations or experimental comparisons of limited scale and scope. In this study, a comprehensive effort is made to identify appropriate values of the FPA parameters that maximize its computational performance. To serve this goal, a simple non-iterative, single-stage sampling tuning method is employed, oriented towards practical applications of FPA. The tuning method is applied to the set of 28 functions specified in IEEE-CEC'13 for real-parameter single-objective optimization problems. It is found that the optimal FPA parameters depend significantly on the objective functions, the problem dimensions and affordable computational cost. Furthermore, it is found that the FPA parameters that minimize mean prediction errors do not always offer the most robust predictions. At the end of this study, recommendations are made for setting the optimal FPA parameters as a function of problem dimensions and affordable computational cost. [Abstract copyright: © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.]

Item Type: Article
Keywords (uncontrolled): Parameters tuning, Flower pollination algorithm, Optimization, Evolutionary, Metaheuristics
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 33929
Notes on copyright: This is a post-peer-review, pre-copyedit version of an article published in Soft Computing. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00500-021-06230-1
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Depositing User: Jisc Publications Router
Date Deposited: 06 Oct 2021 10:14
Last Modified: 29 Nov 2022 17:39
URI: https://eprints.mdx.ac.uk/id/eprint/33929

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