Buzzard Optimization Algorithm: A Nature-Inspired Metaheuristic Algorithm

سال انتشار: 1398
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 134

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شناسه ملی سند علمی:

JR_MJEE-13-3_009

تاریخ نمایه سازی: 25 بهمن 1401

چکیده مقاله:

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.

نویسندگان

Ali Arshaghi

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

Mohsen Ashourian

Department of Electrical Engineering, Majlesi Branch, Islamic Azad University

Leila Ghabeli

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

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