As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

Throughout the centuries, nature has been a source of inspiration, with much still to learn
from and discover about. Among many others, Swarm Intelligence (SI), a substantial branch …

Optimization techniques, particularly meta-heuristic algorithms, are highly effective in
optimizing and enhancing efficiency across diverse models and systems, renowned for their …

From the past few decades many nature inspired algorithms have been developed and
gaining more popularity because of their effectiveness in solving problems of distinct …

Recently, the numerical optimization field has attracted the research community to propose
and develop various metaheuristic optimization algorithms. This paper presents a new …

This paper proposes a novel population-based optimization method, called Aquila Optimizer
(AO), which is inspired by the Aquila's behaviors in nature during the process of catching the …

The development of efficient optimization algorithms is crucial across various scientific
disciplines. As the complexity and diversity of optimization problems continue to grow …

There is a need for some techniques to solve various problems in today's computing world.
Metaheuristic algorithms are one of the techniques which are capable of providing practical …

This paper introduces the Human Evolutionary Optimization Algorithm (HEOA), a
metaheuristic algorithm inspired by human evolution. HEOA divides the global search …

In this research, a new optimized deep learning-based methodology is proposed for optimal
and efficient modeling of the Proton-exchange membrane fuel cells. Here, a hybrid method …