2014 / xviii + 494 pages / hardcover / ISBN: 978-1-611973-42-6 / List Price $125.00 / SIAM Member Price $87.50 / Order Code MO16
Keywords: mathematical programming, stochastic optimization, convex analysis, risk analysis, modeling uncertainty
This second edition replaces Lectures on Stochastic Programming: Modeling and Theory (MP09, ISBN 9780898716870), which is no longer available.
Optimization problems involving stochastic models occur in almost all areas of science and engineering, such as telecommunications, medicine, and finance. Their existence compels a need for rigorous ways of formulating, analyzing, and solving such problems. This book focuses on optimization problems involving uncertain parameters and covers the theoretical foundations and recent advances in areas where stochastic models are available.
In Lectures on Stochastic Programming: Modeling and Theory, Second Edition, the authors introduce new material to reflect recent developments in stochastic programming:
This book is intended for researchers working on theory and applications of optimization. It also is suitable as a text for advanced graduate courses in optimization.
About the Authors
Alexander Shapiro is a Professor in the School of Industrial and Systems Engineering at Georgia Institute of Technology. He has published more than 100 articles in peer-reviewed journals and is the coauthor of several books.
Darinka Dentcheva is a Professor of Mathematics at Stevens Institute of Technology. She works in the areas of decisions under uncertainty, convex analysis, and stability of optimization problems.
Andrzej Ruszczyński is a Professor of Operations Research at Rutgers University. His research is devoted to the theory and methods of optimization under uncertainty and risk.
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