Spider Monkey Optimization Algorithm

Part of the Studies in Computational Intelligence book series (SCI, volume 779)


Foraging behavior of social creatures has always been a matter of study for the development of optimization algorithms. Spider Monkey Optimization (SMO) is a global optimization algorithm inspired by Fission-Fusion social (FFS) structure of spider monkeys during their foraging behavior. SMO exquisitely depicts two fundamental concepts of swarm intelligence: self-organization and division of labor. SMO has gained popularity in recent years as a swarm intelligence based algorithm and is being applied to many engineering optimization problems. This chapter presents the Spider Monkey Optimization algorithm in detail. A numerical example of SMO procedure has also been given for a better understanding of its working.


Spider monkey optimization Swarm intelligence Fission-fusion social structure Numerical optimization 


  1. 1.
    Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York, NY (1999)zbMATHGoogle Scholar
  2. 2.
    Bansal, J.C., Sharma, H., Jadon, S.S., Clerc, M.: Spider monkey optimization algorithm for numerical optimization. Memetic Comput. 6(1), 31–47 (2014)CrossRefGoogle Scholar
  3. 3.
    Dhar, J., Arora, S.: Designing fuzzy rule base using spider monkey optimization algorithm in cooperative framework. Future Comput. Info. J. 2(1), 31–38 (2017). ISSN 2314-7288CrossRefGoogle Scholar
  4. 4.
    Sharma, A., Sharma, H., Bhargava, A., et al.: Memetic Comp. 9, 311 (2017). Scholar
  5. 5.
    Wu, H., Yan, Y., Liu, C., Zhang, J.: Pattern synthesis of sparse linear arrays using spider monkey optimization. In: IEICE Transactions on Communications, Released 01 March 2017Google Scholar
  6. 6.
    Cheruku, R., Edla, D.R., Kuppili, V.: SM-RuleMiner: Spider monkey based rule miner using novel fitness function for diabetes classification. Comput. Biol. Med. 81, 79–92 (2017)CrossRefGoogle Scholar
  7. 7.
    Al-Azza, A.A., Al-Jodah, A.A., Harackiewicz, F.J.: Spider monkey optimization: a novel technique for antenna optimization. IEEE Antennas Wirel. Propag. Lett. 15, 1016–1019 (2016)CrossRefGoogle Scholar
  8. 8.
    Couzin, I.D, Laidre, M.E: Fission–fusion populations. Curr. Biol. 19(15), R633–R635CrossRefGoogle Scholar
  9. 9.
  10. 10.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Rajasthan Technical UniversityKotaIndia
  2. 2.South Asian UniversityNew DelhiIndia

Personalised recommendations