Bat algorithm (BA): review, applications and modifications

Authors

  • Amar Yahya Zebari computer science
  • Saman M. Almufti Statistics
  • Chyavan Mohammed Abdulrahman Physical Education and Sport Sciences,

DOI:

https://doi.org/10.14419/ijsw.v8i1.30120

Keywords:

Swarm Intelligence (SI), Bat Algorithm (BA), Literature Review, Metaheuristic Algorithm.

Abstract

Generally, Metaheuristic algorithms such as ant colony optimization, Elephant herding algorithm, particle swarm optimization, bat algorithms becomes a powerful methods for solving optimization problems. This paper provides a timely review of the bat algorithm and its new variants.

Bat algorithm (BA) is a Swarm based metaheuristic algorithm developed in 2010 by Xin-She Yang, BA has been inspired by the foraging behavior of micro bats, algorithm carries out the search process using artiï¬cial bats as search agents mimicking the natural pulse loudness and emission rate of real bats. It has become a powerful swarm intelligence method for solving optimization prob-lems over continuous and discrete spaces. Nowadays, it has been successfully applied to solve problems in almost all areas of opti-mization, and it found to be very efficient. As a result, the literature has expanded significantly, a wide range of diverse applications and case studies has been made base on the bat algorithm.

 

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2020-01-23

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