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Buzzard Optimization Algorithm: A Nature-Inspired Metaheuristic Algorithm

عنوان مقاله: Buzzard Optimization Algorithm: A Nature-Inspired Metaheuristic Algorithm
شناسه ملی مقاله: JR_MJEE-13-3_009
منتشر شده در در سال 1398
مشخصات نویسندگان مقاله:

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

خلاصه 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.

کلمات کلیدی:
Buzzard Optimization Algorithm, global optimization, benchmark, Bio Inspired Meta-Heuristic

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1603865/