Slime Mould Algorithm for Solving Ambulance Dispatching Problem

Khelfa, Celia; Khennak, Ilyes; Drias, Habiba; Drias, Yassine; Belharda, Yagoub; Smail, Mehrez

doi:10.1007/978-3-031-27524-1_80

Cited by 5 publications

(1 citation statement)

References 18 publications

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“…Rifat Md Sayed Hasan et al [115] applied the presented BSMA for solving the unit commitment problem (UCP). Khelfa C et al [120] used an SMA to improve the response time for an ambulance dispatching problem. Mehrtash Eskandaripour et al [121] proposed a SWMM-SMA model to design a low-impact development (LID) approach for urban area management practices.…”

Section: Engineering Optimization Problemmentioning

confidence: 99%

Advances in Slime Mould Algorithm: A Comprehensive Survey

Wei,

Othman,

Daud

et al. 2024

Biomimetics

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The slime mould algorithm (SMA) is a new swarm intelligence algorithm inspired by the oscillatory behavior of slime moulds during foraging. Numerous researchers have widely applied the SMA and its variants in various domains in the field and proved its value by conducting various literatures. In this paper, a comprehensive review of the SMA is introduced, which is based on 130 articles obtained from Google Scholar between 2022 and 2023. In this study, firstly, the SMA theory is described. Secondly, the improved SMA variants are provided and categorized according to the approach used to apply them. Finally, we also discuss the main applications domains of the SMA, such as engineering optimization, energy optimization, machine learning, network, scheduling optimization, and image segmentation. This review presents some research suggestions for researchers interested in this algorithm, such as conducting additional research on multi-objective and discrete SMAs and extending this to neural networks and extreme learning machining.

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Section: Engineering Optimization Problemmentioning

confidence: 99%