Review
Version 1
Preserved in Portico This version is not peer-reviewed
Advances in Slime Mould Algorithm: A comprehensive Survey
Version 1
: Received: 8 September 2023 / Approved: 8 September 2023 / Online: 8 September 2023 (10:34:24 CEST)
A peer-reviewed article of this Preprint also exists.
Wei, Y.; Othman, Z.; Daud, K.M.; Luo, Q.; Zhou, Y. Advances in Slime Mould Algorithm: A Comprehensive Survey. Biomimetics 2024, 9, 31. Wei, Y.; Othman, Z.; Daud, K.M.; Luo, Q.; Zhou, Y. Advances in Slime Mould Algorithm: A Comprehensive Survey. Biomimetics 2024, 9, 31.
Abstract
Slime Mould Algorithm (SMA) is a new swarm intelligence algorithm inspired by the oscillatory behavior of slime molds during foraging. Numerous researchers have widely applied SMA and its variants in various domains and proved its value by the experiments in literatures. In this paper a comprehensive survey on SMA is introduced, which is based on 130 articles visa Google-scholar between 2022 and July, 2023. Firstly, the theory of SMA is described. Secondly the improved SMA variants are provided and categorized according to the approach that they are applied with. Finally, it also discusses the main applications domains of SMA such as engineering optimization, energy optimization, machine learning, network, scheduling optimization, image segmentation and etc. This review presents some research suggestion for researcher who is interested in this algorithm.
Keywords
slime mould algorithm (SMA); swarm intelligence; optimization; Metaheuristic algorithm
Subject
Computer Science and Mathematics, Data Structures, Algorithms and Complexity
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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