Foraging-Inspired Optimisation Algorithms (Natural Computing Series) - Tapa dura

Brabazon, Anthony; McGarraghy, Seán

 
9783319591551: Foraging-Inspired Optimisation Algorithms (Natural Computing Series)
Tapa dura
ISBN 10: 331959155X ISBN 13: 9783319591551
Editorial: Springer, 2018

Sinopsis

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.

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Acerca del autor

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 industry in areas such as financial mathematics, financial economics, and computer science. He is cofounder and codirector of the Natural Computing Research and Applications Group at UCD, among the most successful research groups dedicated to this subject. Among his publications are the successful coauthored books 'Natural Computing Algorithms', 'Foundations in Grammatical Evolution for DynamicEnvironments', and 'Biologically Inspired Algorithms for Financial Modelling'. 

Dr. Seán McGarraghy is the director of the UCD Centre for Business Analytics, he was formerly director of the UCD Smurfit Graduate School of Business MSc in Business Analytics. He has qualifications in electronics, mathematics and management and his teaching and academic publications cover many aspects of business analytics and operations research. Particular topics of interests include combinatorial enumeration and optimization, network algorithms, supply chain management, quadratic forms and K-theory. Among his publications are the successful coauthored book 'Natural Computing Algorithms'.

De la contraportada

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2018
Idioma
Inglés
ISBN 10 
331959155X
ISBN 13 
9783319591551
Encuadernación
Tapa dura
Número de edición
1
Número de páginas
498
Contacto del fabricante
no disponible
Persona responsable
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Friedrich-Karl-Str. 9
Hamburg
Alemania

Otras ediciones populares con el mismo título

9783030096403: Foraging-Inspired Optimisation Algorithms (Natural Computing Series)

Edición Destacada

ISBN 10:  3030096408 ISBN 13:  9783030096403
Editorial: Springer, 2019
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