Stochastic Linear Programming

Models, Theory, and Computation

  • Peter Kall
  • János Mayer

Part of the International Series in Operations Research & Management Science book series (ISOR, volume 80)

Table of contents

  1. Front Matter
    Pages i-5
  2. Pages 7-73
  3. Pages 193-272
  4. Pages 273-374
  5. Back Matter
    Pages 375-397

About this book


Peter Kall and János Mayer are distinguished scholars and professors of Operations Research and their research interest is particularly devoted to the area of stochastic optimization. STOCHASTIC LINEAR PROGRAMMING: Models, Theory, and Computation is a definitive presentation and discussion of the theoretical properties of the models, the conceptual algorithmic approaches, and the computational issues relating to the implementation of these methods to solve problems that are stochastic in nature. The application area of stochastic programming includes portfolio analysis, financial optimization, energy problems, random yields in manufacturing, risk analysis, etc. In this book models in financial optimization and risk analysis are discussed as examples, including solution methods and their implementation.

Stochastic programming is a fast developing area of optimization and mathematical programming. Numerous papers and conference volumes, and several monographs have been published in the area; however, the Kall & Mayer book will be particularly useful in presenting solution methods including their solid theoretical basis and their computational issues, based in many cases on implementations by the authors. The book is also suitable for advanced courses in stochastic optimization.


algorithm algorithms linear optimization mathematical programming modeling nonlinear optimization operations research optimization programming

Authors and affiliations

  • Peter Kall
    • 1
  • János Mayer
    • 1
  1. 1.University of ZürichSwitzerland

Bibliographic information