Optimization in Electrical Engineering
This textbook provides students, researchers, and engineers in the area of electrical engineering with advanced mathematical optimization methods. Presented in a readable format, this book highlights fundamental concepts of advanced optimization used in electrical engineering.  Chapters provide a collection that ranges from simple yet important concepts such as unconstrained optimization to highly advanced topics such as linear matrix inequalities and artificial intelligence-based optimization methodologies. The reader is motivated to engage with the content via numerous application examples of optimization in the area of electrical engineering. The book begins with an extended review of linear algebra that is a prerequisite to mathematical optimization. It then precedes with unconstrained optimization, convex programming, duality, linear matrix inequality, and intelligent optimization methods. This book can be used as the main text in courses such as Engineering Optimization, Convex Engineering Optimization, Advanced Engineering Mathematics and Robust Optimization and will be useful for practicing design engineers in electrical engineering fields. Author provided cases studies and worked examples are included for student and instructor use.

"1133676673"
Optimization in Electrical Engineering
This textbook provides students, researchers, and engineers in the area of electrical engineering with advanced mathematical optimization methods. Presented in a readable format, this book highlights fundamental concepts of advanced optimization used in electrical engineering.  Chapters provide a collection that ranges from simple yet important concepts such as unconstrained optimization to highly advanced topics such as linear matrix inequalities and artificial intelligence-based optimization methodologies. The reader is motivated to engage with the content via numerous application examples of optimization in the area of electrical engineering. The book begins with an extended review of linear algebra that is a prerequisite to mathematical optimization. It then precedes with unconstrained optimization, convex programming, duality, linear matrix inequality, and intelligent optimization methods. This book can be used as the main text in courses such as Engineering Optimization, Convex Engineering Optimization, Advanced Engineering Mathematics and Robust Optimization and will be useful for practicing design engineers in electrical engineering fields. Author provided cases studies and worked examples are included for student and instructor use.

74.49 In Stock
Optimization in Electrical Engineering

Optimization in Electrical Engineering

Optimization in Electrical Engineering

Optimization in Electrical Engineering

eBook1st ed. 2019 (1st ed. 2019)

$74.49  $99.00 Save 25% Current price is $74.49, Original price is $99. You Save 25%.

Available on Compatible NOOK devices, the free NOOK App and in My Digital Library.
WANT A NOOK?  Explore Now

Related collections and offers


Overview

This textbook provides students, researchers, and engineers in the area of electrical engineering with advanced mathematical optimization methods. Presented in a readable format, this book highlights fundamental concepts of advanced optimization used in electrical engineering.  Chapters provide a collection that ranges from simple yet important concepts such as unconstrained optimization to highly advanced topics such as linear matrix inequalities and artificial intelligence-based optimization methodologies. The reader is motivated to engage with the content via numerous application examples of optimization in the area of electrical engineering. The book begins with an extended review of linear algebra that is a prerequisite to mathematical optimization. It then precedes with unconstrained optimization, convex programming, duality, linear matrix inequality, and intelligent optimization methods. This book can be used as the main text in courses such as Engineering Optimization, Convex Engineering Optimization, Advanced Engineering Mathematics and Robust Optimization and will be useful for practicing design engineers in electrical engineering fields. Author provided cases studies and worked examples are included for student and instructor use.


Product Details

ISBN-13: 9783030053093
Publisher: Springer-Verlag New York, LLC
Publication date: 03/01/2019
Sold by: Barnes & Noble
Format: eBook
File size: 20 MB
Note: This product may take a few minutes to download.

About the Author

Mohammad Fathi received the M.Sc. and Ph.D. degrees in electrical engineering from the Amirkabir University of Technology, Tehran, Iran, in 2003 and 2010, respectively. From 2003 to 2006, he was a Lecturer with the Department of Electrical Engineering, University of Kurdistan, Faculty of Engineering, Sanandaj, Iran, where he is currently working as an Associate Professor. From February 2010 to November 2010, he conducted part of his Ph.D. research work in the Communications and Networking Theory Laboratory, Royal Institute of Technology, Stockholm, Sweden. His current research interests include power scheduling, smart grid communications and control, network resource allocation, and optimization.

Hassan Bevrani received a PhD degree in electrical engineering from Osaka University in 2004. Currently, he is a full professor and the Program Leader of Micro/Smart Grids Research Center (SMGRC) at the University of Kurdistan. Over the years, he has worked with Osaka University, Kumamoto University (Japan), Queensland University of Technology (Australia), Kyushu Institute of Technology, Centrale Lille (France), and Technical University of Berlin (Germany). He is the author of 6 international books, 15 book chapters, and more than 300 journal/conference papers. He has been the guest editor of 3 volumes of Elsevier Energy Procedia journal. His current research interests include optimization, smart grid operation and control, power system stability, Microgrid dynamics and control, and Intelligent/robust control applications in power electric industry.    

 

Table of Contents

Introduction.- Linear Algebra Review.- Set constrained Optimization.- Convex Programming.- Duality.- LMI-based Optimization.- Artificial intelligence and evolutionary algorithms based optimization

From the B&N Reads Blog

Customer Reviews