Advanced Optimization and Operations Research
This textbook provides students with fundamentals and advanced concepts in optimization and operations research. It gives an overview of the historical perspective of operations research and explains its principal characteristics, tools, and applications.
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Asoke Kumar Bhunia Laxminarayan Sahoo Ali Akbar Shaikh
Advanced Optimization and Operations Research
Springer Optimization and Its Applications Volume 153 Series Editor Panos M. Pardalos
, University of Florida, Gainesville, FL, USA
Honorary Editor Ding-Zhu Du, University of Texas at Dallas, Richardson, TX, USA Advisory Editors J. Birge, University of Chicago, Chicago, IL, USA S. Butenko, Texas A&M University, College Station, TX, USA F. Giannessi, University of Pisa, Pisa, Italy S. Rebennack, Karlsruhe Institute of Technology, Karlsruhe, Baden-Württemberg, Germany T. Terlaky, Lehigh University, Bethlehem, PA, USA Y. Ye, Stanford University, Stanford, CA, USA
Aims and Scope Optimization has continued to expand in all directions at an astonishing rate. New algorithmic and theoretical techniques are continually developing and the diffusion into other disciplines is proceeding at a rapid pace, with a spot light on machine learning, artificial intelligence, and quantum computing. Our knowledge of all aspects of the field has grown even more profound. At the same time, one of the most striking trends in optimization is the constantly increasing emphasis on the interdisciplinary nature of the field. Optimization has been a basic tool in areas not limited to applied mathematics, engineering, medicine, economics, computer science, operations research, and other sciences. The series Springer Optimization and Its Applications (SOIA) aims to publish state-of-the-art expository works (monographs, contributed volumes, textbooks, handbooks) that focus on theory, methods, and applications of optimization. Topics covered include, but are not limited to, non-linear optimization, combinatorial optimization, continuous optimization, stochastic optimization, Bayesian optimization, optimal control, discrete optimization, multi-objective optimization, and more. New to the series portfolio include Works at the intersection of optimization and machine learning, artificial intelligence, and quantum computing. Volumes from this series are indexed by Web of Science, zbMATH, Mathematical Reviews, and SCOPUS.
More information about this series at http://www.springer.com/series/7393
Asoke Kumar Bhunia Laxminarayan Sahoo Ali Akbar Shaikh •
Advanced Optimization and Operations Research
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Asoke Kumar Bhunia Department of Mathematics The University of Burdwan Burdwan, West Bengal, India
Laxminarayan Sahoo Department of Mathematics Raniganj Girls’ College Raniganj, West Bengal, India
Ali Akbar Shaikh Department of Mathematics The University of Burdwan Burdwan, West Bengal, India
ISSN 1931-6828 ISSN 1931-6836 (electronic) Springer Optimization and Its Applications ISBN 978-981-32-9966-5 ISBN 978-981-32-9967-2 (eBook) https://doi.org/10.1007/978-981-32-9967-2 Mathematics Subject Classification (2010): 90Cxx, 90Bxx, 91Axx, 90B05 © Springer Nature Singapore Pte Ltd. 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translati
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