Semi-Steady-State Jaya Algorithm for Optimization

Uday K. Chakraborty

doi:10.3390/APP10155388

Semi-Steady-State Jaya Algorithm for Optimization

Uday K. Chakraborty

University of Missouri-St. Louis

Research output: Contribution to journal › Article › peer-review

Abstract

The Jaya algorithm is arguably one of the fastest-emerging metaheuristics amongst the newest members of the evolutionary computation family. The present paper proposes a new, improved Jaya algorithm by modifying the update strategies of the best and the worst members in the population. Simulation results on a twelve-function benchmark test-suite and a real-world problem show that the proposed strategy produces results that are better and faster in the majority of cases. Statistical tests of significance are used to validate the performance improvement.

Original language	American English
Journal	Applied Sciences
Volume	10
DOIs	https://doi.org/10.3390/APP10155388
State	Published - Aug 4 2020

Disciplines

Computer Sciences
Theory and Algorithms

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Cite this

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