In this article, we encompass an analysis of the recent advances in parallel genetic
algorithms (PGAs). We have selected these algorithms because of the deep interest in many …

The increasing complexity of real-world optimization problems raises new challenges to
evolutionary computation. Responding to these challenges, distributed evolutionary …

The economic development of numerous countries is defined by maritime supply chains to a
great extent. Substantial volumes of containerized cargoes delivered by ships are handled …

The intertwined processes of learning and evolution in complex environmental niches have
resulted in a remarkable diversity of morphological forms. Moreover, many aspects of animal …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

Abstract Machine learning research has advanced in multiple aspects, including model
structures and learning methods. The effort to automate such research, known as AutoML …

A gravitational search algorithm (GSA) uses gravitational force among individuals to evolve
population. Though GSA is an effective population-based algorithm, it exhibits low search …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

Security risk assessment and mitigation are two vital processes that need to be executed to
maintain a productive IT infrastructure. On one hand, models such as attack graphs and …

Surrogate assisted global optimization is gaining popularity. Similarly, modern advances in
computing power increasingly rely on parallelization rather than faster processors. This …