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Moth-Flame Optimization Algorithm: Variants and Applications - 2020


Moth–Flame Optimization Algorithm | S - Logix

Research Area:  Metaheuristic Computing

Abstract:

This paper thoroughly presents a comprehensive review of the so-called moth–flame optimization (MFO) and analyzes its main characteristics. MFO is considered one of the promising metaheuristic algorithms and successfully applied in various optimization problems in a wide range of fields, such as power and energy systems, economic dispatch, engineering design, image processing and medical applications. This manuscript describes the available literature on MFO, including its variants and hybridization, the growth of MFO publications, MFO application areas, theoretical analysis and comparisons of MFO with other algorithms. Conclusions focus on the current work on MFO, highlight its weaknesses, and suggest possible future research directions. Researchers and practitioners of MFO belonging to different fields, like the domains of optimization, medical, engineering, clustering and data mining, among others will benefit from this study.

Keywords:  
moth–flame optimization
power energy systems
economic dispatch
engineering design
image processing
medical applications

Author(s) Name:  Mohammad Shehab, Laith Abualigah, Husam Al Hamad, Hamzeh Alabool, Mohammad Alshinwan & Ahmad M. Khasawneh

Journal name:  Neural Computing and Applications

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/s00521-019-04570-6

Volume Information:  Volume 32