Nature Inspired Computing and Optimization

. Ed(s): Patnaik, Srikanta; Yang, Xin-She; Nakamatsu, Kazumi

ISBN 10: 3319509195 / ISBN 13: 9783319509198

Published by Springer International Publishing AG, 2017

Editor(s): Patnaik, Srikanta; Yang, Xin-She; Nakamatsu, Kazumi. Series: Modeling and Optimization in Science and Technologies. Num Pages: 494 pages, 148 black & white illustrations, 43 colour illustrations, biography. BIC Classification: PBU; UMB; UYM. Category: (P) Professional & Vocational. Dimension: 235 x 155. . . 2017. 1st ed. 2017. Hardback. . . . . Seller Inventory # V9783319509198

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.

From the Back Cover:

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.

Bibliographic Details

Title: Nature Inspired Computing and Optimization
Publisher: Springer International Publishing AG
Publication Date: 2017
Binding: Hardcover
Condition: New
Edition: 1st Edition