Editors:
- 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
- Includes supplementary material: sn.pub/extras
Part of the book series: Modeling and Optimization in Science and Technologies (MOST, volume 10)
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Table of contents (19 chapters)
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Front Matter
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.
Keywords
- Antenna Array Design
- Bio-Inspired Computing
- Ant Colony Optimisation
- Bat Algorithm
- Classifier System
- Cuckoo Search
- Economic Dispatch
- Flower Pollination Algorithm
- Genetic Algorithm
- Image Enhancement
- Swarm Intelligence
- Nature-Inspired Algorithm
- Wireless Sensor Network
- Multi-Agent Systems
- Permutation Problems
- Particle Swarm Optimization
- Resource Planning
- Swarm-Based Heuristics
- Multi-Objective Optimization
- Engineering Economics
Editors and Affiliations
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Dept of Computer Science and Engineering, SOA University Dept of Computer Science and Engineering, Bhubaneswar, India
Srikanta Patnaik
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School of Science and Technology, Middlesex University School of Science and Technology, London, United Kingdom
Xin-She Yang
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School of H.S.E., University of Hyogo School of H.S.E., Himeji, Japan
Kazumi Nakamatsu
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
DOI: https://doi.org/10.1007/978-3-319-50920-4
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-50919-8Published: 16 March 2017
Softcover ISBN: 978-3-319-84522-7Published: 08 May 2018
eBook ISBN: 978-3-319-50920-4Published: 07 March 2017
Series ISSN: 2196-7326
Series E-ISSN: 2196-7334
Edition Number: 1
Number of Pages: XXI, 494
Number of Illustrations: 148 b/w illustrations, 43 illustrations in colour
Topics: Computational Intelligence, Optimization, Artificial Intelligence, Simulation and Modeling, Engineering Economics, Organization, Logistics, Marketing