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Spider Monkey Optimization Algorithm

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

Abstract

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.

Keywords

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

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  • DOI: 10.1007/978-3-319-91341-4_4
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Fig. 1

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Correspondence to Jagdish Chand Bansal .

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Sharma, H., Hazrati, G., Bansal, J.C. (2019). Spider Monkey Optimization Algorithm. In: Bansal, J., Singh, P., Pal, N. (eds) Evolutionary and Swarm Intelligence Algorithms. Studies in Computational Intelligence, vol 779. Springer, Cham. https://doi.org/10.1007/978-3-319-91341-4_4

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