Metaheuristic optimization algorithms are global optimization approaches that manage the
search process to efficiently explore search spaces associated with different optimization …

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 …

In this paper, an adaptive Harris hawk optimization with persistent trigonometric (sine–
cosine)-differences (ADHHO) is proposed for parameter identification of Photovoltaic (PV) …

The Henry Gas Solubility Optimization (HGSO) is a physics-based metaheuristic inspired by
Henry's law, which describes the solubility of the gas in a liquid under specific pressure …

Nature-inspired metaheuristic algorithms are gaining popularity with their easy applicability
and ability to avoid local optimum points, and they are spreading to wide application areas …

In this article, a new prairie dog optimization algorithm (PDOA) is analyzed to realize the
optimum economic design of three well-known heat exchangers. These heat exchangers …

Chaotic maps have the characteristics of ergodicity and non-repeatability. Owing to these
properties, they provide fast convergence by effectively scanning the search space in a …

Monkey king evolution (MKE) is a population-based differential evolutionary algorithm in
which the single evolution strategy and the control parameter affect the convergence and the …

Thermal system optimization is always a challenging task due to several constraints and
critical concepts of thermo-hydraulic aspects. Heat exchangers are one of those devices that …

A reliable methodology is essential for accurately estimating the parameters of PV models,
enabling reliable performance evaluations, effective control studies, accurate analysis of …