Optimization is a searching technique by which we can find the best solution from all the
feasible solutions. There are two types of optimization problems depending up on the type of …

Because of successful implementations and high intensity, metaheuristic research has been
extensively reported in literature, which covers algorithms, applications, comparisons, and …

This book exemplifies how algorithms are developed by mimicking nature. Classical
techniques for solving day-to-day problems is time-consuming and cannot address complex …

A metaheuristic is a collection of algorithmic frameworks inspired by nature designed to
provide the fittest nearoptimal solution for optimization problems (Marqas et al., 2020) …

It is obvious from wider spectrum of successful applications that metaheuristic algorithms are
potential solutions to hard optimization problems. Among such algorithms are swarm-based …

This paper presents a quick review of the basic concepts and essential steps for
implementing of metaheuristic algorithms. It can be therefore used as a roadmap to shed …

Research in metaheuristics for global optimization problems are currently experiencing an
overload of wide range of available metaheuristic-based solution approaches. Since the …

In the area of optimization, metaheuristic algorithms have attracted a lot of interest. For many
centuries, human beings have utilized metaheuristic algorithms as a problem-solving …

Metaheuristic optimization is a higher-level optimization that uses a simple and efficient
procedure to solve optimization problems. Metaheuristic can understand higher-level …

In recent years, metaheuristics (MHs) have become important tools for solving hard
optimization problems encountered in industry, engineering, biomedical, image processing …