Nature-Inspired Computing and Optimization | Theory and Applications

Srikanta Patnaik (u. a.)

ISBN 10: 3319845225 / ISBN 13: 9783319845227

Published by Springer, 2018

About this Item

Nature-Inspired Computing and Optimization | Theory and Applications | Srikanta Patnaik (u. a.) | Taschenbuch | Modeling and Optimization in Science and Technologies | xxi | Englisch | 2018 | Springer | EAN 9783319845227 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 114238499

Bibliographic Details

• Title: Nature-Inspired Computing and Optimization | Theory and Applications
• Publisher: Springer
• Publication Date: 2018
• Language: English
• ISBN 10: 3319845225
• ISBN 13: 9783319845227
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 28D millimeters 235 millimeters width by 155 millimeters height by 28 millimeters depth
• Weight: 774 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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.