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Moth Flame Optimization: Theory, Modifications, Hybridizations, and Applications
https://orcid.org/0000-0002-2203-4549
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.
Moth Flame Optimization: Theory, Modifications, Hybridizations, and Applications
https://orcid.org/0000-0002-2203-4549
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.
Moth Flame Optimization: Theory, Modifications, Hybridizations, and Applications
https://orcid.org/0000-0002-2203-4549
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.
Moth Flame Optimization: Theory, Modifications, Hybridizations, and Applications
Sahoo, Saroj Kumar (author) / Saha, Apu Kumar (author) / Ezugwu, Absalom E. (author) / Agushaka, Jeffrey O. (author) / Abuhaija, Belal (author) / Alsoud, Anas Ratib (author) / Abualigah, Laith (author)
2022
Article (Journal)
Electronic Resource
English
Energy Efficient Clustering Protocol for FANETS Using Moth Flame Optimization
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Design of Supervised and Blind Channel Equalizer Based on Moth-Flame Optimization
| Springer Verlag | 2018
| British Library Online Contents | 2017