• 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

  • Pages
    16
  • From page
    83
  • To page
    98
  • 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
  • Serial Year
    2019
  • Journal title
    Majlesi Journal of Electrical Engineering
  • Record number

    2484327