A mayfly optimization algorithm

•An efficient powerful optimization method (MA) is presented.•Performance of MA is checked for benchmark both continuous and discrete functions.•MA performs fine on multiobjective optimization.•MA is very competitive with other state-of-the-art optimization algorithms. This paper introduces a new me...

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Veröffentlicht in:Computers & industrial engineering Jg. 145; S. 106559
Hauptverfasser: Zervoudakis, Konstantinos, Tsafarakis, Stelios
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.07.2020
Schlagworte:
Mayfly algorithm
Nature-inspired algorithm
Optimization
Mayfly algorithm
Optimization
Nature-inspired algorithm
ISSN:0360-8352, 1879-0550
Online-Zugang:Volltext
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Zusammenfassung:•An efficient powerful optimization method (MA) is presented.•Performance of MA is checked for benchmark both continuous and discrete functions.•MA performs fine on multiobjective optimization.•MA is very competitive with other state-of-the-art optimization algorithms. This paper introduces a new method called the Mayfly Algorithm (MA) to solve optimization problems. Inspired from the flight behavior and the mating process of mayflies, the proposed algorithm combines major advantages of swarm intelligence and evolutionary algorithms. To evaluate the performance of the proposed algorithm, 38 mathematical benchmark functions, including 13 CEC2017 test functions, are employed and the results are compared to those of seven state of the art well-known metaheuristic optimization methods. The MA’s performance is also assessed through convergence behavior in multi-objective optimization as well as using a real-world discrete flow-shop scheduling problem. The comparison results demonstrate the superiority of the proposed method in terms of convergence rate and convergence speed. The processes of nuptial dance and random flight enhance the balance between algorithm’s exploration and exploitation properties and assist its escape from local optima.
ISSN:0360-8352
1879-0550
DOI:10.1016/j.cie.2020.106559