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Big Data Optimization: Recent Developments and Challenges

Artikelnummer: 978-3-319-30263-8
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The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

"It can be used as a reference book on big data, to obtain a broad view of the direction and landscape. In addition, it can be used by specialists in specific areas of big data, especially optimization-related areas. In this respect, the preview of chapter titles and brief explanations provided in this review reveal specific areas of interest for the intended specialists. I like this edited volume and recommend it." (M. M. Tanik, Computing Reviews, January, 2017)


EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.

The main objective of this book is to provide the necessary background to work with big data by introducing some novel optimization algorithms and codes capable of working in the big data setting as well as introducing some applications in big data optimization for both academics and practitioners interested, and to benefit society, industry, academia, and government. Presenting applications in a variety of industries, this book will be useful for the researchers aiming to analyses large scale data. Several optimization algorithms for big data including convergent parallel algorithms, limited memory bundle algorithm, diagonal bundle method, convergent parallel algorithms, network analytics, and many more have been explored in this book.

"It can be used as a reference book on big data, to obtain a broad view of the direction and landscape. In addition, it can be used by specialists in specific areas of big data, especially optimization-related areas. In this respect, the preview of chapter titles and brief explanations provided in this review reveal specific areas of interest for the intended specialists. I like this edited volume and recommend it." (M. M. Tanik, Computing Reviews, January, 2017)


EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.

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VerlagSpringer EN
EinbandFester Einband
Erscheinungsjahr2016
Seitenangabe502 S.
AusgabekennzeichenEnglisch
AbbildungenXV, 487 p. 182 illus., 160 illus. in color., farbige Illustrationen, schwarz-weiss Illustrationen
MasseH23.5 cm x B15.5 cm 8'749 g
CoverlagSpringer (Imprint/Brand)
Auflage1st ed. 2016
ReiheStudies in Big Data
AutorEmrouznejad, Ali (Hrsg.)

Alle Bände der Reihe "Studies in Big Data"

Über den Autor Ali (Hrsg.) Emrouznejad

Ali Emrouznejad is Professor and Chair in Business Analytics at Surrey Business School, UK, and Director of the Centre for Business Analytics in Practice. His research focuses on performance measurement, efficiency and productivity analysis, artificial intelligence, and big data. He has published over 250 articles in leading journals and has been listed among the world's top 2% most influential scientists by Stanford University. He is Editor of the Springer book series Business Analytics in Practice and has authored or edited numerous books. Professor Emrouznejad also serves as editor, associate editor, or member of the editorial boards of several scientific journals. Subhash C. Ray is a Professor of Economics at the University of Connecticut, USA, where he has been a faculty member since 1982. He earned his Ph.D. in Economics from the University of California, and earlier degrees from the University of Calcutta and the Indian Institute of Management Calcutta. His research focuses on production analysis, efficiency measurement, and econometrics, with a particular emphasis on Data Envelopment Analysis (DEA). He is the author of the widely cited book Data Envelopment Analysis: Theory and Techniques for Economics and Operations Research (Cambridge University Press, 2004) and serves as an Associate Editor of the Journal of Productivity Analysis. Professor Ray has published numerous papers in top-ranked academic journals in economics, operations research, and productivity analysis. Professor Gokulananda Patel is an accomplished academic specializing in Decision Sciences, Applied Mathematics, and Operations Research. He holds a Master's degree in Applied Mathematics and a Ph.D. in Operations Research. Currently, he serves as a Professor of Decision Sciences at Birla Institute of Management Technology India. With an extensive research portfolio, Prof. Patel has published over 70 research papers, primarily focusing on Data Envelopment Analysis and its applications in performance evaluation and operational efficiency. Beyond his institutional roles, he has also contributed as a visiting professor, sharing his expertise in quantitative methods, operations research, and decision sciences with academic communities across the globe.

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