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Application of Jaya Algorithm and Its Variants on Constrained and Unconstrained Benchmark Functions

  • Ravipudi Venkata RaoEmail author
Chapter
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Abstract

This chapter presents the results of application of Jaya algorithm and its variants like SAMP-Jaya and SAMPE-Jaya algorithms on 15 unconstrained benchmark functions given in CEC 2015 as well as 15 other unconstrained functions and 5 constrained benchmark functions. The results are compared with those given by the other well known optimization algorithms. The results have shown the satisfactory performance of Jaya algorithm and its variants for the considered CEC 2015 benchmark functions and the other constrained and unconstrained optimization problems. The statistical tests have also supported the performance supremacy of the variants of the Jaya algorithm.

Keywords

Jaya Algorithm Unconstrained Benchmark Problems Fully Informed Particle Swarm (FIPS) Particle Swarm Optimization Learning Algorithm Maximum Function Evaluations 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringS.V. National Institute of TechnologySuratIndia

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