This research article presents the Multi-Objective Hippopotamus Optimizer (MOHO), a
unique approach that excels in tackling complex structural optimization problems. The …

Introducing a novel meta-heuristic optimization algorithm, the Flood Algorithm (FLA) draws
inspiration from the intricate movement and flow patterns of water masses during flooding …

In recent algorithmic family simulates different biological processes observed in Nature in
order to efficiently address complex optimization problems. In the last years the number of …

The novelty of this article lies in introducing a novel stochastic technique named the
Hippopotamus Optimization (HO) algorithm. The HO is conceived by drawing inspiration …

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 …

The proposed paper introduces a new optimization algorithm inspired by nature called the
polar fox optimization algorithm (PFA). This algorithm addresses the herd life of polar foxes …

This paper introduces a novel approach, the Modified Electric Eel Foraging Optimization
(EELFO) algorithm, which integrates artificial neural networks (ANNs) with metaheuristic …

In recent decades, there has been an increasing interest from the research community in
various scientific and engineering fields, including robotic control, signal processing, image …

In recent years, the application of Deep Learning (DL) for damage detection in Structural
Health Monitoring (SHM) using time-series data has garnered significant attention from the …

Metaheuristic algorithms are increasingly utilized to solve complex optimization problems
because they can efficiently explore large solution spaces. The moss growth optimization …