Modeling with Stochastic Programming (Hardcover)

Alan J. King

ISBN 10: 3031545494 / ISBN 13: 9783031545498

Published by Springer International Publishing AG, Cham, 2024

About this Item

Hardcover. This is an updated version of what is still the only text to address basic questions about how to model uncertainty in mathematical programming, including how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This second edition has important extensions regarding how to represent random phenomena in the models (also called scenario generation) as well as a new chapter on multi-stage models.This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental modeling issues are. The book is easy-to-read, highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty.Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York.Stein W. Wallace is a Professor of Operational Research and head of Center for Shipping and Logistics at NHH Norwegian School of Economics, Bergen, Norway. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty.Alan King is a Research Staff Member at IBM's Thomas J. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783031545498

Bibliographic Details

• Title: Modeling with Stochastic Programming (Hardcover)
• Publisher: Springer International Publishing AG, Cham
• Publication Date: 2024
• Language: English
• ISBN 10: 3031545494
• ISBN 13: 9783031545498
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: new

About this title

Synopsis

This is an updated version of what is still the only text to address basic questions about how to model uncertainty in mathematical programming, including how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This second edition has important extensions regarding  how to represent random phenomena in the models (also called scenario generation) as well as a new chapter on multi-stage models.

This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental modeling issues are. 

The book is easy-to-read, highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty.

Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York.

Stein W. Wallace is a Professor of Operational Research and head of Center for Shipping and Logistics at NHH Norwegian School of Economics, Bergen, Norway.

About the Author

Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York.

Stein W. Wallace is a Professor of Operational Research and head of Center for Shipping and Logistics at NHH Norwegian School of Economics, Bergen, Norway.