Moth Flame Optimization: Theory, Modifications, Hybridizations, and Applications
Document Type
Article
Publication Date
1-1-2023
Abstract
The Moth flame optimization (MFO) algorithm belongs to the swarm intelligence family and is applied to solve complex real-world optimization problems in numerous domains. MFO and its variants are easy to understand and simple to operate. However, these algorithms have successfully solved optimization problems in different areas such as power and energy systems, engineering design, economic dispatch, image processing, and medical applications. A comprehensive review of MFO variants is presented in this context, including the classic version, binary types, modified versions, hybrid versions, multi-objective versions, and application part of the MFO algorithm in various sectors. Finally, the evaluation of the MFO algorithm is presented to measure its performance compared to other algorithms. The main focus of this literature is to present a survey and review the MFO and its applications. Also, the concluding remark section discusses some possible future research directions of the MFO algorithm and its variants.
Publication Title
Archives of Computational Methods in Engineering
First Page Number
391
Last Page Number
426
DOI
10.1007/s11831-022-09801-z
Recommended Citation
Sahoo, Saroj Kumar; Saha, Apu Kumar; Ezugwu, Absalom E.; Agushaka, Jeffrey O.; Abuhaija, Belal; Alsoud, Anas Ratib; and Abualigah, Laith, "Moth Flame Optimization: Theory, Modifications, Hybridizations, and Applications" (2023). Kean Publications. 462.
https://digitalcommons.kean.edu/keanpublications/462