Open AccessSocial Spider Optimization Algorithm: Theory and its Applications
Author(s) -
D. Evangeline,
T. Abirami
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.i8261.0881019
Subject(s) - swarm intelligence , computer science , swarm behaviour , algorithm , variety (cybernetics) , optimization algorithm , heuristic , basis (linear algebra) , artificial intelligence , mathematical optimization , particle swarm optimization , mathematics , geometry
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