Buzzard Optimization Algorithm: A Nature-Inspired Metaheuristic Algorithm

Majlesi Journal of Electrical Engineering

مقاله 9، دوره 13، شماره 3، آذر 2019، صفحه 83-98   

نوع مقاله: Review Article

نویسندگان

Ali Arshaghi¹؛ Mohsen Ashourian^{* 2}؛ Leila Ghabeli³

¹Department of Electrical Engineering, Central Tehran Branch, Islamic Azad University, Tehran

²Department of Electrical Engineering, Majlesi Branch, Islamic Azad University

³Department of Electrical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran

چکیده

Various algorithms have proposed during the last decade for solving different complex optimization problems. The meta-heuristic algorithms have been highly noted among researchers. In this paper, a new algorithm, known as the Buzzards Optimization Algorithm (BUZOA), is introduced. Marvelous and special lifestyle of buzzards and their competition characteristics for prey has been the basic motivation for this new optimization algorithm. The algorithm performance has been compared with newest and well-known meta-heuristics on some benchmark problems and test functions. Results have shown the high performance of the proposed BUZOA compared to the other well known algorithms.

کلیدواژه‌ها

Buzzard Optimization Algorithm؛ global optimization؛ benchmark؛ Bio Inspired Meta-Heuristic

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