Review of Evolutionary Algorithms based on parallel computing paradigm
|International Journal of Computer Science and Engineering|
|© 2017 by SSRG - IJCSE Journal|
|Volume 4 Issue 6|
|Year of Publication : 2017|
|Authors : Bhanu Prakash Lohani, Vimal Bibhu, Ajit Singh|
How to Cite?
Bhanu Prakash Lohani, Vimal Bibhu, Ajit Singh, "Review of Evolutionary Algorithms based on parallel computing paradigm," SSRG International Journal of Computer Science and Engineering , vol. 4, no. 6, pp. 1-4, 2017. Crossref, https://doi.org/10.14445/23488387/IJCSE-V4I6P101
Evolutionary algorithms are used to find the optimal solution for the real world problem based upon the concept of biological evolution. When the data size is very large and fitness function is complex in nature at that time sequential evolutionary algorithms fails to give satisfactory result in the given time domain. Hence the parallelization is done to that can handle the complex real world optimization problems in the reasonable time. Parallelization is a process which is used to do speed up to the existing system to provide the result in the required time frame. In this paper we have presented the review of various evolutionary algorithms studied for the literature review for the research work. We had also summarized Why parallelization is needed for any evolutionary algorithm how we can implement the parallelization with the help of Hadoop Map reduce architecture. We have also presented a comparative result analysis of Particle swarm optimization algorithm. The parallel version of Particle swarm optimization is implemented with the help of Hadoop MR Architecture.
Evolutionary algorithm, Swarm, Parallelization, optimization, Hadoop, biological evolution, mutation.
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