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

Metaheuristic algorithms are widely known as efficient solutions for solving problems of
optimization. These algorithms supply powerful instruments with significant engineering …

The whale optimization algorithm (WOA) is a prominent problem solver which is broadly
applied to solve NP-hard problems such as feature selection. However, it and most of its …

This work presents a novel nature-inspired metaheuristic called Nutcracker Optimization
Algorithm (NOA) inspired by Clark's nutcrackers. The nutcrackers exhibit two distinct …

In order to effectively schedule railway train delay, an adaptive cooperative co-evolutionary
differential evolution with dynamic hybrid mechanism of the quantum evolutionary algorithm …

In this paper, a new bio-inspired metaheuristic algorithm called Zebra Optimization
Algorithm (ZOA) is developed; its fundamental inspiration is the behavior of zebras in nature …

This work presents a new nature-inspired meta-heuristic algorithm named spider wasp
optimization (SWO) algorithm, which is based on replicating the hunting, nesting, and mating …

Despite the simplicity of the whale optimization algorithm (WOA) and its success in solving
some optimization problems, it faces many issues. Thus, WOA has attracted scholars' …

Developing countries have had numerous obstacles in diagnosing the COVID-19 worldwide
pandemic since its emergence. One of the most important ways to control the spread of this …

Feature selection (FS) represents an optimization problem that aims to simplify and improve
the quality of highly dimensional datasets through selecting prominent features and …