Social Spider Optimization Algorithm: Theory and its Applications

  • Evangeline D
  • et al.
Citations of this article
Mendeley users who have this article in their library.
Get full text


An extensive variety of optimization problems are solved by swarm intelligence algorithms that are modelled based on the animal or insect behaviour while living in groups. One such recent swarm intelligence algorithm is Social Spider Optimization (SSO). This paper thoroughly reviews and analyses the characteristics of this meta-heuristic algorithm. Since the existing literature of this algorithm is comparatively limited, the paper discusses the research ideas presented in such existing works and classifies the literature on basis of the application areas like image processing, optical flow, electric circuits, neural networks and basic sciences. It also sets a basis for research applications of the algorithm in order to tap the complete potential of the algorithm in other areas to achieve desired results.




Evangeline, D., & Abirami, Dr. T. (2019). Social Spider Optimization Algorithm: Theory and its Applications. International Journal of Innovative Technology and Exploring Engineering, 8(10), 327–332.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free