Modeling with Stochastic Programming

by Alan J. King, Stein W. Wallace

Overview

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 shastic 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.

Product Details

ISBN-13:	9783031545498
Publisher:	Springer International Publishing
Publication date:	06/01/2024
Series:	Springer Series in Operations Research and Financial Engineering
Edition description:	Second Edition 2024
Pages:	202
Product dimensions:	6.10(w) x 9.25(h) x (d)

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.

Table of Contents

Uncertainty in Optimization.- Information Structures and Feasibility.- Modeling the Objective Function.- Scenario Tree Generation, With Michal Kaut and Jamie Fairbrother.- High-Dimentional Dependent Randomness. With Zhaoxia Guo and Michal Kaut.- Service Network Design, With Arnt-Gunnar Lium and Teodor Gabriel Crainic.- A Multi-dimensional Newsboy Problem with Substitution, With Hajnalka Vaagen.- References.- Index.

Editorial Reviews

From the reviews:

“It is the first book that systematically tries to answer the questions about modeling under uncertainty … . The book is written in a very readable style … . An experienced researcher who is already familiar with optimization under uncertainty will benefit from reading this book … .” (Laura Galli, Interfaces, Vol. 43 (5), September-October, 2013)

“The book is intended as a textbook for graduate students and researchers interested in decision making under uncertainty. It is expected that the book will also be suitable for teaching some operations research courses for undergraduates. … this textbook can indeed be very useful for mathematics students as a methodological guide to the applications of shastic programming methods. The structure of the textbook is well adapted to teaching purposes.” (A. H. Žilinskas, Mathematical Reviews, January, 2013)

From the Publisher