Bat algorithm (BA): review, applications and modifications

 
 
 
  • Abstract
  • Keywords
  • References
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  • 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 artificial 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.

     


  • Keywords


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

  • References


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Article ID: 30120
 
DOI: 10.14419/ijsw.v8i1.30120




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