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Lightning search algorithm: a comprehensive survey.

Laith AbualigahMohamed Abd ElazizAbdelazim G HussienBisan AlsalibiSeyed Mohammad Jafar JalaliAmir H Gandomi
Published in: Applied intelligence (Dordrecht, Netherlands) (2020)
The lightning search algorithm (LSA) is a novel meta-heuristic optimization method, which is proposed in 2015 to solve constraint optimization problems. This paper presents a comprehensive survey of the applications, variants, and results of the so-called LSA. In LSA, the best-obtained solution is defined to improve the effectiveness of the fitness function through the optimization process by finding the minimum or maximum costs to solve a specific problem. Meta-heuristics have grown the focus of researches in the optimization domain, because of the foundation of decision-making and assessment in addressing various optimization problems. A review of LSA variants is displayed in this paper, such as the basic, binary, modification, hybridization, improved, and others. Moreover, the classes of the LSA's applications include the benchmark functions, machine learning applications, network applications, engineering applications, and others. Finally, the results of the LSA is compared with other optimization algorithms published in the literature. Presenting a survey and reviewing the LSA applications is the chief aim of this survey paper.
Keyphrases
  • machine learning
  • deep learning
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  • decision making
  • systematic review
  • cross sectional
  • randomized controlled trial
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