Introduction to Stochastic Programming John R. Birge and Francois Louveaux are an English-language textbook in operations research. It focuses on developing optimal decisions under uncertainty, with extensive attention to models and methods in stochastic programming.
This book provides a clear introduction and is suitable for students and professionals with a basic knowledge of linear programming, analysis, and probability calculus. The content includes, among other things, new approaches for discrete variables, risk measures, Monte Carlo sampling, and the relationship to other methods such as robust optimization and approximate dynamic programming.
The extensively updated new edition covers current developments and includes numerous examples, exercises, and chapter summaries, making it a valuable reference for research and practice in operations research and optimization.
Topics closely aligned with this title include, among others, operational research, probability and statistics, and BUSINESS & ECONOMICS / Operations Research.
Series: Springer Series in Operations Research and Financial Engineering