Mathematical programming and meta-heuristics are two types of optimization methods. Meta-
heuristic algorithms can identify optimal/near-optimal solutions by mimicking natural …

Meta-heuristic algorithms have a high position among academic researchers in various
fields, such as science and engineering, in solving optimization problems. These algorithms …

Recently, many metaheuristic optimization algorithms have been developed to address real-
world issues. In this study, a new physics-based metaheuristic called Fick's law optimization …

In this paper, a new stochastic optimization algorithm is introduced, called Driving Training-
Based Optimization (DTBO), which mimics the human activity of driving training. The …

In this paper, a parameter adaptation-based ant colony optimization (ACO) algorithm based
on particle swarm optimization (PSO) algorithm with the global optimization ability, fuzzy …

Image segmentation is one of the most significant and required procedures in pre-
processing and analyzing images. Metaheuristic optimization algorithms are used to solve a …

Nowadays, meta-heuristic algorithms are attracting widespread interest in solving high-
dimensional nonlinear optimization problems. In this paper, a COVID-19 prevention-inspired …

The development and expansion of the Internet and cyberspace have increased computer
systems attacks; therefore, Intrusion Detection Systems (IDSs) are needed more than ever …

This paper introduces a new human-based metaheuristic algorithm called Sewing Training-
Based Optimization (STBO), which has applications in handling optimization tasks. The …

Abstract The Tunicate Swarm Algorithm (TSA) inspires by simulating the lives of Tunicates at
sea and how food is obtained. This algorithm is easily entrapped to local optimization …