Glowworm swarm optimization, Optimization, Swarm intelligence, Clustering

Abstract

This paper reviews glowworm swarm optimization algorithm (GSO), which is a meta-heuristic swarm intelligence algorithm. The GSO algorithm is applied for solving optimization problems. Shortcoming of the GSO algorithm has been identified with the introduction and discussion of the improvement taken place in recent years. Adaptive step size and new movement rules have been widely used in the improvement of GSO algorithm. The application of GSO including clustering techniques is also presented. Very promising GSO clustering versions use MapReduce framework to improve the computational efficiency when the clustered data set is large and thereby reducing the time complexity.