An Overview of Ant Colony Optimization Algorithms for Dynamic Optimization Problems

Abstract

In recent years, computer scientists have discovered that the complex social behaviors of ants might serve as models for tackling challenging combinatorial optimization issues. Ant colony optimization (ACO) is the most effective and best-recognized metaheuristic based on ant behavior. It was motivated by one characteristic of ant behavior, the capacity to locate what computer scientists would term shortest pathways. This book will be full of new ideas about the ACO algorithm and its future path. This book aims to provide a comprehensive overview of these rapidly expanding topics, from their theoretical genesis to practical implementations, as well as explanations of numerous existing ACO variants and their real-world applications. Furthermore, challenging and recent optimization problems will be considered to optimally solve using the current variants of ACO with respect to other existing optimizers in the literature. Academic and industrial researchers, graduate students, and scholars interested in learning how to apply the ACO algorithm and its variants will be interested in this book.