In recent years, significant research has been done to solve optimization and complex
problems by metaheuristic algorithms. Metaheuristic algorithms are inspired by the …

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 …

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 …

Preoperative differentiation of complicated and uncomplicated appendicitis is challenging.
The research goal was to construct a new intelligent diagnostic rule that is accurate, fast …

Meta-heuristic algorithms have been widely used to solve different optimization problems.
There have always been ongoing efforts to develop new and efficient algorithms. In this …

Abstract Though the Butterfly Bptimization Algorithm (BOA) has already proved its
effectiveness as a robust optimization algorithm, it has certain disadvantages. So, a new …