Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications (International Series in Operations Research & Management Science, 46)

ISBN 10: 0792374630 / ISBN 13: 9780792374633

Published by Springer, 2019

About this Item

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Bibliographic Details

• Title: Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications (International Series in Operations Research & Management Science, 46)
• Publisher: Springer
• Publication Date: 2019
• Language: English
• ISBN 10: 0792374630
• ISBN 13: 9780792374633
• Binding: Hardcover
• Condition: good

About this title

Synopsis

Modeling Uncertainty: An Examination of Stochastic Theory, Methods, and Applications, is a volume undertaken by the friends and colleagues of Sid Yakowitz in his honor. Fifty internationally known scholars have collectively contributed 30 papers on modeling uncertainty to this volume. Each of these papers was carefully reviewed and in the majority of cases the original submission was revised before being accepted for publication in the book. The papers cover a great variety of topics in probability, statistics, economics, stochastic optimization, control theory, regression analysis, simulation, stochastic programming, Markov decision process, application in the HIV context, and others. There are papers with a theoretical emphasis and others that focus on applications. A number of papers survey the work in a particular area and in a few papers the authors present their personal view of a topic. It is a book with a considerable number of expository articles, which are accessible to a nonexpert - a graduate student in mathematics, statistics, engineering, and economics departments, or just anyone with some mathematical background who is interested in a preliminary exposition of a particular topic. Many of the papers present the state of the art of a specific area or represent original contributions which advance the present state of knowledge. In sum, it is a book of considerable interest to a broad range of academic researchers and students of stochastic systems.

About the Author

​Moshe Dror joined the Eller College of Management in 1990 and previously taught at Ben Gurion University. He earned his PhD in Management Science from the University of Maryland in 1983. His research focuses on cooperative game theory, cost allocation in inventory and supply chain management, applied combinatorial optimization in transportation, logistics and manufacturing and intelligent solution systems for operations scheduling.

Pierre L’Ecuyer is a Professor in the Departement d’Informatique et de Recherche Operationnelle at the Universite de Montreal, since 1990. He holds the Canada Research Chair in Stochastic Simulation and Optimization since 2004 and an Inria International Chair (at Inria-Rennes, France) for 2013–2018. He is a member of the CIRRELT and GERAD research centers, in Montreal.

Ferenc Szidarovszky is a senior researcher with the Ridgetop Group Inc. working on theoretical issues concerning reliability, robustness, optimal maintenance and replacement policies and prognostics in complex systems. In addition to these industrial applications he also performs research in systems theory, especially in dynamic economic systems. He has performed research in very broad fields of applied mathematics including numerical analysis, optimization, multi-objective programming, game theory, dynamic systems, applied probability and their applications in industrial processes, environment, water resources management, economics, and computer network security, among others. He currently has a professor position with the Applied Mathematics Department of the University of Pecs, Hungary, where his duty is a one week long intensive Game Theory Course every year.