Nature-Inspired Computing and Optimization : Theory and Applications

Srikanta Patnaik

ISBN 10: 3319509195 / ISBN 13: 9783319509198

Published by Springer International Publishing, 2017

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783319509198

Bibliographic Details

• Title: Nature-Inspired Computing and Optimization : Theory and Applications
• Publisher: Springer International Publishing
• Publication Date: 2017
• Language: English
• ISBN 10: 3319509195
• ISBN 13: 9783319509198
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 34D millimeters 241 millimeters width by 160 millimeters height by 34 millimeters depth
• Weight: 934 grams

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.