Synopsis
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, including: an analytical description of the tangent and normal cones of chance constrained sets; analysis of optimality conditions applied to nonconvex problems; a discussion of the stochastic dual dynamic programming method; an extended discussion of law invariant coherent risk measures and their Kusuoka representations; and in-depth analysis of dynamic risk measures and concepts of time consistency, including several new results.
Audience: 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.
Contents: List of Notations; Preface to the Second Edition; Preface to the First Edition; Chapter 1: Stochastic Programming Models; Chapter 2: Two-Stage Problems; Chapter 3: Multistage Problems; Chapter 4: Optimization Models with Probabilistic Constraints; Chapter 5: Statistical Inference; Chapter 6: Risk Averse Optimization; Chapter 7: Background Material; Chapter 8: Bibliographical Remarks; Bibliography; Index.
"synopsis" may belong to another edition of this title.
About the Author
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 Ruszczynski is a Professor of Operations Research at Rutgers University. His research is devoted to the theory and methods of optimization under uncertainty and risk.
"About this title" may belong to another edition of this title.
Search results for Lectures on Stochastic Programming: Modeling and Theory
Stock Image
Lectures on Stochastic Programming (Hardcover)
Published by
Society for Industrial & Applied Mathematics,U.S., New York, 2014
ISBN 10: 1611973422
ISBN 13: 9781611973426
New
Hardcover
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. Optimization problems involving stochastic models occur in most areas of science and engineering, particularly telecommunications, medicine, and finance. Their existence reveals 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 this second edition, the authors introduce new material to reflect recent developments, including: analytical descriptions of the tangent and normal cones of chance constrained sets; analysis of optimality conditions for nonconvex problems; a discussion of the stochastic dual dynamic programming method; an extended discussion of law invariant coherent risk measures and their Kusuoka representations; and an in-depth analysis of dynamic risk measures and concepts of time consistency, including several new results. This book is intended for researchers working in optimization. It is also suitable for advanced graduate courses in this area. Optimization problems involving stochastic models occur in most areas of science, revealing a need for rigorous ways of analyzing and solving such problems. This new edition focuses on theoretical foundations and recent developments, including new material on optimality conditions for nonconvex problems, law invariant coherent risk measures, and more. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781611973426
Stock Image
Lectures on Stochastic Programming (Hardcover)
Published by
Society for Industrial & Applied Mathematics,U.S., New York, 2014
ISBN 10: 1611973422
ISBN 13: 9781611973426
New
Hardcover
Seller: AussieBookSeller, Truganina, VIC, Australia
Seller rating 5 out of 5 stars
Hardcover. Condition: new. Hardcover. Optimization problems involving stochastic models occur in most areas of science and engineering, particularly telecommunications, medicine, and finance. Their existence reveals 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 this second edition, the authors introduce new material to reflect recent developments, including: analytical descriptions of the tangent and normal cones of chance constrained sets; analysis of optimality conditions for nonconvex problems; a discussion of the stochastic dual dynamic programming method; an extended discussion of law invariant coherent risk measures and their Kusuoka representations; and an in-depth analysis of dynamic risk measures and concepts of time consistency, including several new results. This book is intended for researchers working in optimization. It is also suitable for advanced graduate courses in this area. Optimization problems involving stochastic models occur in most areas of science, revealing a need for rigorous ways of analyzing and solving such problems. This new edition focuses on theoretical foundations and recent developments, including new material on optimality conditions for nonconvex problems, law invariant coherent risk measures, and more. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9781611973426