Title of article :
Buzzard Optimization Algorithm: A Nature-Inspired Metaheuristic Algorithm
Author/Authors :
Arshaghi ، Ali Department of Electrical Engineering - Islamic Azad University, Central Tehran Branch , Ashourian ، Mohsen Department of Electrical Engineering - Islamic Azad University, Majlesi Branch , Ghabeli ، Leila Department of Electrical Engineering - Islamic Azad University, Central Tehran Branch
Abstract :
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.
Keywords :
Buzzard Optimization Algorithm , Global Optimization , Benchmark , Bio Inspired Meta , Heuristic
Journal title :
Majlesi Journal of Electrical Engineering
Journal title :
Majlesi Journal of Electrical Engineering
