An Approach of Adjusting the Switch Probability based on Dimension Size: A Case Study for Performance Improvement of the Flower Pollination Algorithm

dc.contributor.authorAziz, Tahsin
dc.contributor.authorMuhammad, Tashreef
dc.contributor.authorChowdhury, Md Rashedul Karim
dc.contributor.authorAlam, Mohammad Shafiul
dc.date.accessioned2024-12-05T22:23:49Z
dc.date.available2024-12-05T22:23:49Z
dc.date.issued2022-08-20
dc.descriptionThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
dc.description.abstractNumerous meta-heuristic algorithms have been influenced by nature. Over the past couple of decades, their quantity has been significantly escalating. The majority of these algorithms attempt to emulate natural biological and physical phenomena. This research concentrates on the Flower Pollination algorithm, which is one of several bio-inspired algorithms. The original approach was suggested for pollen grain exploration and exploitation in confined space using a specific global pollination and local pollination strategy. As a “swarm intelligence" meta-heuristic algorithm, its strength lies in locating the vicinity of the optimum solution rather than identifying the minimum. A modification to the original method is detailed in this work. This research found that by changing the specific value of “switch probability" with dynamic values of different dimension sizes and functions, the outcome was mainly improved over the original flower pollination method.
dc.identifier.citationAziz, T., Muhammad, T., Chowdhury, M. R. K., & Alam, M. S. (2022). An Approach of Adjusting the Switch Probability based on Dimension Size: A Case Study for Performance Improvement of the Flower Pollination Algorithm. arXiv preprint arXiv:2208.09699.
dc.identifier.urihttps://hdl.handle.net/10294/16570
dc.language.isoen
dc.publisherarXiv
dc.subjectSwarm Intelligence
dc.subjectMeta-heuristic Algorithm
dc.subjectLocal Pollination
dc.subjectGlobal Pollination
dc.subjectFlower Pollination Algorithm
dc.subjectSwitch Probability
dc.titleAn Approach of Adjusting the Switch Probability based on Dimension Size: A Case Study for Performance Improvement of the Flower Pollination Algorithm
dc.typePreprint

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