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A Study on Optimization Algorithms for Clustering Gene Expression Data

Athul Jose, Chandrasekar P

Data clustering has been studied for a long time and every day trends are proposed for better outcomes in this field. Optimization is the process of selecting the best solutions from a set of solution. Many number of optimization algorithms are available now a days. This paper deals mainly with Genetic Algorithm, Particle Swarm Optimization and Nelder Mead method. Brief workings of the above mentioned algorithms are provided in the paper. Almost all optimization algorithms are nature inspired. Genetic algorithm deals with evolution of living organism and particle swarm optimization was developed inspired by bird flocks. Nelder Mead simplex is an optimization technique based on mathematical figures.