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Krill Herd Algorithm (KHA)

  • Babak Zolghadr-Asli
  • Omid Bozorg-Haddad
  • Xuefeng Chu
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 720)

Abstract

The krill herd algorithm (KHA) is a new metaheuristic search algorithm based on simulating the herding behavior of krill individuals using a Lagrangian model. This algorithm was developed by Gandomi and Alavi (2012) and the preliminary studies illustrated its potential in solving numerous complex engineering optimization problems. In this chapter, the natural process behind a standard KHA is described.

References

  1. Bolaji, A. L. A., Al-Betar, M. A., Awadallah, M. A., Khader, A. T., & Abualigah, L. M. (2016). A comprehensive review: Krill Herd algorithm (KH) and its applications. Applied Soft Computing, 49, 437–446.Google Scholar
  2. Brierley, A. S., & Cox, M. J. (2010). Shapes of krill swarms and fish schools emerge as aggregation members avoid predators and access oxygen. Current Biology, 20(19), 1758–1762.Google Scholar
  3. Fattahi, E., Bidar, M., & Kanan, H. R. (2016). Fuzzy krill herd (FKH): An improved optimization algorithm. Intelligent Data Analysis, 20(1), 153–165.Google Scholar
  4. Flierl, G., Grünbaum, D., Levins, S., & Olson, D. (1999). From individuals to aggregations: The interplay between behavior and physics. Journal of Theoretical Biology, 196(4), 397–454.Google Scholar
  5. Gandomi, A. H., & Alavi, A. H. (2012). Krill herd: A new bio-inspired optimization algorithm. Communications in Nonlinear Science and Numerical Simulation, 17(12), 4831–4845.MathSciNetMATHGoogle Scholar
  6. Gandomi, A. H., & Alavi, A. H. (2016). An introduction of krill herd algorithm for engineering optimization. Journal of Civil Engineering and Management, 22(3), 302–310.Google Scholar
  7. Gandomi, A. H., Alavi, A. H., & Talatahari, S. (2013a). Structural optimization using krill herd algorithm. Chapter 15 in swarm intelligence and bio-inspired computation: Theory and applications. London, UK: Elsevier Publication.Google Scholar
  8. Gandomi, A. H., Talatahari, S., Tadbiri, F., & Alavi, A. H. (2013b). Krill herd algorithm for optimum design of truss structures. International Journal of Bio-Inspired Computation, 5(5), 281–288.Google Scholar
  9. Gandomi, A. H., Yang, X. S., & Alavi, A. H. (2013c). Cuckoo search algorithm: A metaheuristic approach to solve structural optimization problems. Engineering with Computers, 29(1), 17–35.Google Scholar
  10. Hofmann, E. E., Haskell, A. E., Klinck, J. M., & Lascara, C. M. (2004). Lagrangian modelling studies of Antarctic krill (Euphausia superba) swarm formation. ICES Journal of Marine Science, 61(4), 617–631.Google Scholar
  11. Mandal, B., Roy, P. K., & Mandal, S. (2014). Economic load dispatch using krill herd algorithm. International Journal of Electrical Power & Energy Systems, 57, 1–10.Google Scholar
  12. Mukherjee, A., & Mukherjee, V. (2015). Solution of optimal power flow using chaotic krill herd algorithm. Chaos, Solitons & Fractals, 78, 10–21.MathSciNetGoogle Scholar
  13. Price, H. J. (1989). Swimming behavior of krill in response to algal patches: A mesocosm study. Limnology and Oceanography, 34(4), 649–659.Google Scholar
  14. Wang, G. G., Gandomi, A. H., & Alavi, A. H. (2013). A chaotic particle-swarm krill herd algorithm for global numerical optimization. Kybernetes, 42(6), 962–978.MathSciNetGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Irrigation and Reclamation Engineering, Faculty of Agricultural Engineering and Technology, College of Agriculture and Natural ResourcesUniversity of TehranKarajIran
  2. 2.Department of Civil and Environmental EngineeringNorth Dakota State UniversityFargoUSA

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