Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …

Metaheuristic algorithms can be summarized as a form of stochastic optimization algorithm
which does not depend on the surface gradient for optimization. These algorithms draw …

Recent advances in metaheuristics have shown the advantages of using the Lévy
distribution, which models a kind of random walk (named “Lévy flight”) with occasional “big” …

With the rapid development of Internet of Things (IoT) technologies, fog computing has
emerged as an extension to the cloud computing that relies on fog nodes with distributed …

Abstract Salp Swarm Algorithm (SSA) is a recent approach with a simple implementation,
few parameters, and low computational cost. SSA has been used in different optimization …

Abstract Crow Search Algorithm (CSA) is a swarm-based single-objective optimizer
proposed in recent years, which tried to inspire the behavior of crows that hide foods in …

In the past years a great variety of nature-inspired algorithms have proven their ability to
efficiently handle combinatorial optimization problems ranging from design and form finding …

In this paper, a new optimization algorithm called Spherical Search (SS) is proposed to
solve the bound-constrained non-linear global optimization problems. The main operations …

Global optimization has been a hot research topic in various engineering applications,
where differential evolution (DE) is one of the most popular approaches. Actually, it is …

In optimization, the performance of differential evolution (DE) and their hybrid versions exist
in the literature is highly affected by the inappropriate choice of its operators like mutation …