Social Spider Optimization Algorithm: Theory and its Applications

  • Evangeline D
  • et al.
N/ACitations
Citations of this article
15Readers
Mendeley users who have this article in their library.
Get full text

Abstract

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.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

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. https://doi.org/10.35940/ijitee.i8261.0881019

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 4

80%

Lecturer / Post doc 1

20%

Readers' Discipline

Tooltip

Business, Management and Accounting 4

57%

Computer Science 1

14%

Social Sciences 1

14%

Chemistry 1

14%

Save time finding and organizing research with Mendeley

Sign up for free