Introduction to Unconstrained Optimization with R - Softcover

Mishra, Shashi Kant; Ram, Bhagwat

 
9789811508967: Introduction to Unconstrained Optimization with R
Softcover
ISBN 10: 9811508968 ISBN 13: 9789811508967
Verlag: Springer-Verlag GmbH, 2021

Inhaltsangabe

This book discusses unconstrained optimization with R―a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture.

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Über die Autorin bzw. den Autor

Shashi Kant Mishra, Ph.D., D.Sc., is Professor at the Department of Mathematics, Institute of Science, Banaras Hindu University, Varanasi, India. With over 20 years of teaching experience, he has authored six books, including textbooks and monographs, and has been on the editorial boards of several respected international journals. He has guest edited special issues of the Journal of Global Optimization and Optimization Letters (both Springer Nature) and Optimization (Taylor & Francis). A DST Fast Track Fellow (2001–2002), Prof. Mishra has published over 150 papers and supervised 15 Ph.D. students. He has visited around 15 institutes/universities in countries such as France, Canada, Italy, Spain, Japan, Taiwan, China, Singapore, Vietnam, and Kuwait.

Bhagwat Ram is a Senior Research Fellow at the DST Centre for Interdisciplinary Mathematical Sciences, Institute of Science, Banaras Hindu University, Varanasi. He holds an M.Sc. in Computer Science, and co-authored the book Introduction to Linear Programming with MATLAB, with Prof. Shashi Kant Mishra. He is currently developing generalized gradient methods to solve unconstrained optimization problems and instructing graduate students in their MATLAB practicals at the Centre for Interdisciplinary Mathematical Sciences at the Banaras Hindu University. He received an international travel grant from the Council of Scientific Industrial and Research, Government of India, to attend a summer school on linear programming at New South Wales University, Australia, in January 2019.

Von der hinteren Coverseite

This book discusses unconstrained optimization with R — a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture.

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Verlag
Springer-Verlag GmbH
Erscheinungsdatum
2021
Sprache
Englisch
ISBN 10 
9811508968
ISBN 13 
9789811508967
Einband
Tapa blanda
Auflage
1
Anzahl der Seiten
304
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
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Weitere beliebte Ausgaben desselben Titels

9789811508936: Introduction to Unconstrained Optimization with R

Vorgestellte Ausgabe

ISBN 10:  9811508933 ISBN 13:  9789811508936
Verlag: Springer-Verlag GmbH, 2020
Hardcover