In this review paper, JAYA algorithm, which is a recent population-based algorithm is
intensively overviewed. The JAYA algorithm combines the survival of the fittest principle from …

Abstract The Jaya Algorithm is a relatively new population-based optimization, which has
become a progressively valuable tool in swarm intelligence. The Jaya algorithm …

In this study, a self-learning discrete Jaya algorithm (SD-Jaya) is proposed to address the
energy-efficient distributed no-idle flow-shop scheduling problem (FSP) in a heterogeneous …

Advancements in medical technology have created numerous large datasets including
many features. Usually, all captured features are not necessary, and there are redundant …

Recent advances in metaheuristics have shown the advantages of using the Lévy
distribution, which models a kind of random walk (named “Lévy flight”) with occasional “big” …

This article presents a comprehensively state-of-the-art investigation of the engineering
applications utilized by binary metaheuristic algorithms. Surveyed work is categorized based …

Abstract Feature Subset Selection (FSS) is an NP-hard problem to remove redundant and
irrelevant features particularly from medical data, and it can be effectively addressed by …

Jaya algorithm (JAYA) is a new metaheuristic algorithm, which has a very simple structure
and only requires population size and terminal condition for optimization. Given the two …

The development of an accurate nitrogen oxide (NO x) prediction model is difficult because
of multiple parameters, strong coupling, and long delay time of selective catalytic reduction …

In order to efficiently solve the binary optimization problems by using differential evolution
(DE), a class of new transfer functions, Taper-shaped transfer function, is firstly proposed by …