Jaya元启发式对基准函数和射频电路的比较研究

Amel Garbaya, M. Kotti, M. Fakhfakh, B. Benhala
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引用次数: 2

摘要

Jaya算法是最近开发出来的。它是一种简单而强大的全局优化算法。与-à-vis其他已知的元启发式算法相比,Jaya算法的主要特点是它只需要很少的控制参数,即代数、总体大小和设计变量的数量。在本文中,我们讨论了Jaya在基准函数和射频电路优化设计中的应用,即低噪声放大器。结果表明,该算法比特定的群优化算法PSO、回溯搜索算法BSA和遗传算法GA具有更好的收敛性。
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Comparative Study of Jaya Metaheuristic to Benchmark Functions and RF Circuits
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.
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