Neural Computing and Applications

, Volume 22, Issue 6, pp 1239–1255

Bat algorithm for constrained optimization tasks

  • Amir Hossein Gandomi
  • Xin-She Yang
  • Amir Hossein Alavi
  • Siamak Talatahari
Original Article

DOI: 10.1007/s00521-012-1028-9

Cite this article as:
Gandomi, A.H., Yang, XS., Alavi, A.H. et al. Neural Comput & Applic (2013) 22: 1239. doi:10.1007/s00521-012-1028-9


In this study, we use a new metaheuristic optimization algorithm, called bat algorithm (BA), to solve constraint optimization tasks. BA is verified using several classical benchmark constraint problems. For further validation, BA is applied to three benchmark constraint engineering problems reported in the specialized literature. The performance of the bat algorithm is compared with various existing algorithms. The optimal solutions obtained by BA are found to be better than the best solutions provided by the existing methods. Finally, the unique search features used in BA are analyzed, and their implications for future research are discussed in detail.


Bat algorithmConstraint optimizationMetaheuristic algorithm

Copyright information

© Springer-Verlag London Limited 2012

Authors and Affiliations

  • Amir Hossein Gandomi
    • 1
  • Xin-She Yang
    • 2
  • Amir Hossein Alavi
    • 3
  • Siamak Talatahari
    • 4
  1. 1.Young Researchers Club, Central Tehran Branch, Islamic Azad UniversityTehranIran
  2. 2.Mathematics and Scientific Computing, National Physical LaboratoryTeddingtonUK
  3. 3.Young Researchers Club, Mashhad Branch, Islamic Azad UniversityMashhadIran
  4. 4.Marand Faculty of Engineering, University of TabrizTabrizIran