This book collects different methodologies that permit metaheuristics and machine learning
to solve real-world problems. This book has exciting chapters that employ evolutionary and …

Based on various sources of inspiration, there are different metaheuristic algorithms, such as
swarm intelligence, evolutionary computation, and bio-inspired algorithms, available in the …

In today's day and time solving real-world complex problems has become fundamentally
vital and critical task. Many of these are combinatorial problems, where optimal solutions are …

This book begins with the basics about nature-inspired optimization techniques and
introduces the methodologies, processes and analytics associated with the same. Due to the …

Metaheuristic algorithms are present in various applications for different domains. Recently,
researchers have conducted studies on the effectiveness of these algorithms in providing …

Metaheuristic optimization methods are widely used to solve complex optimization problems
in various fields such as engineering, finance, and logistics. Evolutionary Algorithms (EAs) …

METAHEURISTICS for MACHINE LEARNING The book unlocks the power of nature-
inspired optimization in machine learning and presents a comprehensive guide to cutting …

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

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 …

The theory of optimization in machine learning has benefited from various fields of research.
Among these, nature-inspired meta-heuristic algorithms are becoming very powerful and …