Foraging-Inspired Optimisation Algorithms [Hardcover]

This book is an introduction to relevant aspects of the foraging literature for algorithmic design, and an overview of key families of optimization algorithms that stem from a foraging metaphor. The authors first offer perspectives on foraging and foraging-inspired algorithms for optimization, they then explain the techniques inspired by the behaviors of vertebrates, invertebrates, and non-neuronal organisms, and they then discuss algorithms based on formal models of foraging, how to evolve a foraging strategy, and likely future developments.

No prior knowledge of natural computing is assumed. This book will be of particular interest to graduate students, academics and practitioners in computer science, informatics, data science, management science, and other application domains.

Introduction.- Formal Models of Foraging.- Sensor Modalities.- Individual and Social Learning.- Introduction to Foraging Algorithms.- Mammals.- Bird Foraging Algorithms.- Fish Algorithms.- Ant Foraging Algorithms.- Honeybee Inspired Algorithms.- Bioluminescence Algorithms.- Spider Algorithms.- Worm Algorithm.- Bacteria Inspired Algorithms.- Slime Mould Foraging.- Plant Foraging Algorithms.- Group Search and Predatory Search.- Evolving Foraging Algorithms.- Conclusions.

Prof. Anthony Brabazon is currently Dean of the UCD College of Business. Previous positions held in UCD include Associate Dean and Director of the Smurfit Graduate School of Business, Vice-Principal of Research and Innovation for the College of Business and Law, and Head of Research for the School of Business. His primary research interests concern the development of natural computing theory and the application of related algorithms to real-world problems, particularly in the domain of business and finance, and he has pioneered multidisciplinary collaborations with industl#œ