Comparative Study of Jaya Metaheuristic to Benchmark Functions and RF Circuits
Amel Garbaya, Mouna Kotti, Mourad Fakhfakh, Bachir Benhala · 2020 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) · 2020
The Jaya algorithm has been recently developed. It is a simple and powerful global optimization algorithm. The main feature of Jaya algorithm vis-à-vis other known metaheuristics algorithms is that it requires only few control parameters namely the number of generations the population size, and the number of design variables. In this paper, we deal with the application of Jaya to a benchmark function and to the optimal design of RF circuits, namely low-noise amplifiers. We show that it has a better convergence than the particular swarm optimization technique PSO, the backtracking search algorithm BSA and the genetic algorithm GA.