A metaheuristic is a collection of algorithmic frameworks inspired by nature designed to
provide the fittest nearoptimal solution for optimization problems (Marqas et al., 2020) …

Swarm based optimization algorithms are a collection of intelligent techniques in the field of
Artificial Intelligence (AI) were developed for simulating the intelligent behavior of animals …

Feature selection and hyper-parameters optimization (tuning) are two of the most important
and challenging tasks in machine learning. To achieve satisfying performance, every …

Abstract The progress of Industrial Revolution 4.0 has been supported by recent advances
in several domains, and one of the main contributors is the Internet of Things. Smart factories …

Metaheuristic algorithms are optimization algorithms that are used to address complicated
issues that cannot be solved using standard approaches. These algorithms are inspired by …

This paper tackles the short-term hydro-power unit commitment problem in a multi-reservoir
system—a cascade-based operation scenario. For this, we propose a new mathematical …

Metaheuristic algorithms have been an interesting and widely used area for scientists,
researchers and academicians because of their specific and significant characteristics and …

Bio-Inspired optimization algorithms are inspired from principles of natural biological
evolution and distributed collective of a living organism such as (insects, animal,…. etc.) for …

Due to the shortcomings of conventional machine hearing methods in tackling data with high-
dimension search space, such as the need for initial configuration and feature extraction …

Metaheuristic is one of the most well-known fields of research used to find optimum solutions
for non-deterministic polynomial hard (NP-hard) problems, for which it is difficult to find an …