In recent years, scholars have developed and enhanced optimization algorithms to tackle
high-dimensional optimization and engineering challenges. The primary challenge of high …

In this paper, a new meta-heuristic optimization algorithm motivated by the foraging
behaviour of blood-sucking leeches in rice fields is presented, named Blood-Sucking Leech …

Recently, multi-resolution pyramid-based techniques have emerged as the prevailing
research approach for image super-resolution. However, these methods typically rely on a …

Particle swarm optimization (PSO) is one of the most classical metaheuristic algorithms that
has gained significant attention since its inception. It has some inherent advantages, such as …

One of the challenges for suppliers is to increase their market share due to the limited target
market. In other words, in the supply chain, the demand for suppliers' products is limited …

In the last few decades, metaheuristic algorithms that use the laws of nature have been used
dramatically in numerous and complex optimization problems. The artificial hummingbird …

This paper examines the performance of three binary metaheuristic algorithms when applied
to two distinct knapsack problems (0–1 knapsack problems (KP01) and multidimensional …

The feature selection problem in multi-view data has garnered widespread attention and
research in recent years, leading to the development of numerous feature selection …

Recent years have seen a growing involvement of researchers and practitioners in crafting
Deep Neural Networks (DNNs) that seem to outperform existing machine learning …

The dynamic of a full-power fuel cell vehicle highly depends on the proton exchange
membrane fuel cell power response. However, when frequent load changes in full-power …