Nature Inspired Computing and Optimization

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

ISBN 10: 3319509195 / ISBN 13: 9783319509198

Editore: 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. . . . . Codice articolo V9783319509198

Riassunto:

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.

Dalla quarta di copertina:

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.

Dati bibliografici

Titolo: Nature Inspired Computing and Optimization
Casa editrice: Springer International Publishing AG
Data di pubblicazione: 2017
Legatura: Rilegato
Condizione: New
Edizione: prima edizione