Stochastic Linear Programming (Ökonometrie und Unternehmensforschung Econometrics and Operations Research)

Peter Kall

ISBN 10: 3540074910 / ISBN 13: 9783540074915

Published by Springer, 1976

About this Item

Springer Verlag; New York, 1976. Hardcover. A Very Good, binding sturdy and intact, spine fade, bumped bottom board corners, mild spine edge wear, bit of age toning to pages, some rubbing to board and spine edges, without Dust wrapper. A nice, clean and unmarked copy. 8vo[octavo or approx. 6 x 9 inches], 95pp., references, indexed. We pack securely and ship daily with delivery confirmation on every book. The picture on the listing page is of the actual book for sale. Additional Scan(s) are available for any item, please inquire.Please note: Oversized books/sets MAY require additional postage then what is quoted for 2.2lb book.

Seller Inventory # SKU1037216

Bibliographic Details

• Title: Stochastic Linear Programming (Ökonometrie und Unternehmensforschung Econometrics and Operations Research)
• Publisher: Springer
• Publication Date: 1976
• Language: English
• ISBN 10: 3540074910
• ISBN 13: 9783540074915
• Binding: hardcover
• Condition: Very Good
• Seller catalogs:
  • Math Text Books

About this title

Synopsis

Todaymanyeconomists, engineers and mathematicians are familiar with linear programming and are able to apply it. This is owing to the following facts: during the last 25 years efficient methods have been developed; at the same time sufficient computer capacity became available; finally, in many different fields, linear programs have turned out to be appropriate models for solving practical problems. However, to apply the theory and the methods of linear programming, it is required that the data determining a linear program be fixed known numbers. This condition is not fulfilled in many practical situations, e. g. when the data are demands, technological coefficients, available capacities, cost rates and so on. It may happen that such data are random variables. In this case, it seems to be common practice to replace these random variables by their mean values and solve the resulting linear program. By 1960 various authors had already recog­ nized that this approach is unsound: between 1955 and 1960 there were such papers as "Linear Programming under Uncertainty", "Stochastic Linear Pro­ gramming with Applications to Agricultural Economics", "Chance Constrained Programming", "Inequalities for Stochastic Linear Programming Problems" and "An Approach to Linear Programming under Uncertainty".

From the Back Cover

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.