Feature selection has become an indispensable machine learning process for data
preprocessing due to the ever-increasing sizes in actual data. There have been many …

The simplicity, transparency, reliability, high efficiency and robust nature of PID controllers
are some of the reasons for their high popularity and acceptance for control in process …

In this paper, a new bio-inspired meta-heuristic algorithm, named artificial rabbits
optimization (ARO), is proposed and tested comprehensively. The inspiration of the ARO …

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

Metaheuristics play a crucial role in solving optimization problems. The majority of such
algorithms are inspired by collective intelligence and foraging of creatures in nature. In this …

This paper presents a novel bio-inspired algorithm inspired by starlings' behaviors during
their stunning murmuration named starling murmuration optimizer (SMO) to solve complex …

Combinatorial optimization is a well-established area in operations research and computer
science. Until recently, its methods have focused on solving problem instances in isolation …

Currently, meta-heuristic algorithms have been widely studied and applied, but balancing
exploration and exploitation remains a challenge. In this study, a novel meta-heuristic …

In the last few years, the formulation of real-world optimization problems and their efficient
solution via metaheuristic algorithms has been a catalyst for a myriad of research studies. In …

This paper proposes a new population-based optimization algorithm called hunter–prey
optimizer (HPO). This algorithm is inspired by the behavior of predator animals such as …