Bat Algorithm and Cuckoo Search: A Tutorial

  • Xin-She Yang
Part of the Studies in Computational Intelligence book series (SCI, volume 427)

Abstract

Nature-inspired metaheuristic algorithms have attracted much attention in the last decade, and new algorithms have emerged almost every year with a vast, ever-expanding literature. In this chapter, we briefly review two latest metaheuristics: bat algorithm and cuckoo search for global optimization. Bat algorithm was proposed by Xin-She Yang in 2010, inspired by the echolocation of microbats, while cuckoo search was developed by Xin-She Yang and Suash Deb in 2009, inspired by the brood parasitism of some cuckoo species. Both algorithms have shown superiority over many other metaheuristics over a wide range of applications.

Keywords

Particle Swarm Optimization Harmony Search Brood Parasitism Pulse Emission Cuckoo Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2013

Authors and Affiliations

  • Xin-She Yang
    • 1
  1. 1.Mathematics & Scientific ComputingNational Physical LaboratoryTeddingtonUK

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