Modeling and Optimization in Science and Technologies

Nature-Inspired Computing and Optimization

Theory and Applications

Editors: Patnaik, Srikanta, Yang, Xin-She, Nakamatsu, Kazumi (Eds.)

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  • Reports on cutting-edge research in nature-inspired computing and optimization
  • Presents a wealth of techniques together with their application to real-world problems
  • Includes theoretical analysis and insights into nature-inspired algorithms
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eBook 118,99 €
price for Spain (gross)
  • ISBN 978-3-319-50920-4
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  • Immediate eBook download after purchase
Hardcover 155,99 €
price for Spain (gross)
  • ISBN 978-3-319-50919-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 155,99 €
price for Spain (gross)
  • ISBN 978-3-319-84522-7
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  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

The book provides readers with a snapshot of the state of the art in the field of nature-inspired computing and its application in optimization. The approach is mainly practice-oriented: each bio-inspired technique or algorithm is introduced together with one of its possible applications. Applications cover a wide range of real-world optimization problems: from feature selection and image enhancement to scheduling and dynamic resource management, from wireless sensor networks and wiring network diagnosis to sports training planning and gene expression, from topology control and morphological filters to nutritional meal design and antenna array design. There are a few theoretical chapters comparing different existing techniques, exploring the advantages of nature-inspired computing over other methods, and investigating the mixing time of genetic algorithms. The book also introduces a wide range of algorithms, including the ant colony optimization, the bat algorithm, genetic algorithms, the collision-based optimization algorithm, the flower pollination algorithm, multi-agent systems and particle swarm optimization. This timely book is intended as a practice-oriented reference guide for students, researchers and professionals.

Table of contents (19 chapters)

Table of contents (19 chapters)
  • The Nature of Nature: Why Nature-Inspired Algorithms Work

    Pages 1-27

    Green, David (et al.)

  • Multimodal Function Optimization Using an Improved Bat Algorithm in Noise-Free and Noisy Environments

    Pages 29-49

    Jamil, Momin (et al.)

  • Multi-objective Ant Colony Optimisation in Wireless Sensor Networks

    Pages 51-78

    Kellner, Ansgar

  • Generating the Training Plans Based on Existing Sports Activities Using Swarm Intelligence

    Pages 79-94

    Fister Jr., Iztok (et al.)

  • Limiting Distribution and Mixing Time for Genetic Algorithms

    Pages 95-122

    Alwadani, S. (et al.)

Buy this book

eBook 118,99 €
price for Spain (gross)
  • ISBN 978-3-319-50920-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 155,99 €
price for Spain (gross)
  • ISBN 978-3-319-50919-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 155,99 €
price for Spain (gross)
  • ISBN 978-3-319-84522-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Nature-Inspired Computing and Optimization
Book Subtitle
Theory and Applications
Editors
  • Srikanta Patnaik
  • Xin-She Yang
  • Kazumi Nakamatsu
Series Title
Modeling and Optimization in Science and Technologies
Series Volume
10
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-50920-4
DOI
10.1007/978-3-319-50920-4
Hardcover ISBN
978-3-319-50919-8
Softcover ISBN
978-3-319-84522-7
Series ISSN
2196-7326
Edition Number
1
Number of Pages
XXI, 494
Number of Illustrations
148 b/w illustrations, 43 illustrations in colour
Topics