Biogeography-Based Optimization: Algorithms and Applications - Hardcover

Zheng, Yujun; Lu, Xueqin; Zhang, Minxia; Chen, Shengyong

Hardcover

ISBN 10: 9811325855 ISBN 13: 9789811325854

Verlag: Springer, 2018

Inhaltsangabe

This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors’ recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.

Über diesen Titel

Über die Autorin bzw. den Autor

Prof. Yujun Zheng received his Ph.D. degree from Institute of Software, Chinese Academy of Science in 2010, and now is Professor and Ph.D. supervisor at College of Computer Science and Technology, Zhejiang University of Technology, China. His research interests include intelligent computing and its application in operations research. He has authored over 60 scientific papers in well-known international journals and conferences. In 2014, he received the runner-up of IFORS Prize for OR Development with the work of biogeography-based optimization for emergency engineering rescue scheduling in disaster relief operations in China.

Dr. Xueqin Lu is a Ph.D. candidate at College of Computer Science and Technology, Zhejiang University of Technology, China. Her main research interests are bio-inspired algorithms and their applications.

Dr. Minxia Zhang is an Associate Professor at College of Computer Science and Technology, Zhejiang University of Technology, China. Her main research interests include bio-inspired computation and its applications.

Dr. Shengyong Chen received his Ph.D. degree from City University of Hong Kong in 2003, and now is Professor, Director of Institute of Computer Vision, at College of Computer Science and Technology, Zhejiang University of Technology, China. His research focuses on computer vision and robotics. Prof. Chen is a recipient of National Outstanding Youth Foundation Award (NSFC) in 2014, IEEE Sensors Journal Best Paper Award in 2012, Research Fellowship of Alexander von Humboldt, Germany in 2006 and is also IET fellow, IEEE senior member.

Von der hinteren Coverseite

This book introduces readers to the background, general framework, main operators, and other basic characteristics of biogeography-based optimization (BBO), which is an emerging branch of bio-inspired computation. In particular, the book presents the authors’ recent work on improved variants of BBO, hybridization of BBO with other algorithms, and the application of BBO to a variety of domains including transportation, image processing, and neural network learning. The content will help to advance research into and application of not only BBO but also the whole field of bio-inspired computation. The algorithms and applications are organized in a step-by-step manner and clearly described with the help of pseudo-codes and flowcharts. The readers will learn not only the basic concepts of BBO but also how to apply and adapt the algorithms to the engineering optimization problems they actually encounter.

Details zur Ausgabe

• Verlag: Springer
• Erscheinungsdatum: 2018
• Sprache: Englisch
• ISBN 10: 9811325855
• ISBN 13: 9789811325854
• Einband: Gebundene Ausgabe
• Auflage: 1
• Anzahl der Seiten: 232
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Tiergartenstr. 17; Heidelberg; 69121; Deutschland