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Stochastic programming. (English) Zbl 1115.90001

Handbooks in Operations Research and Management Science 10. Amsterdam: Elsevier (ISBN 0-444-50854-6/hbk). x, 688 p. (2003).
This excellent Handbook brings together leading experts in stochastic programming to present a rigorous overview of basic models, methods and applications of stochastic programming. The work is intended for researchers, students, engineers and economists, who encounter in their work optimization problems involving uncertainty
Contents: Preface. Andrzej Ruszczyński and Alexander Shapiro, Stochastic programming models (1–64); Andrzej Ruszczyński and Alexander Shapiro, Optimality and duality in stochastic programming (65–139); Andrzej Ruszczyński, Decomposition methods (141–211); François V. Louveaux and Rüdiger Schultz, Stochastic integer programming (213–266); András Prékopa, Probabilistic programming (267–351); Alexander Shapiro, Monte Carlo sampling methods (353–425); G. Ch. Pflug, Stochastic optimization and statistical inference (427–482); Werner Römisch, Stability of stochastic programming problems (483–554); Warren B. Powell and Huseyin Topaloglu, Stochastic programming in transportation and logistics (555–635); Stein W. Wallace and Stein-Erik Fleten, Stochastic programming models in energy (637–677).
Of these ten articles the first presents the necessary background for the following chapters, whereas the last two concentrate on applications. The Handbook articles require a solid mathematical background, especially practitioners should study the introductory article. The Handbook represents a most valuable reference book for experts.

MSC:

90-00 General reference works (handbooks, dictionaries, bibliographies, etc.) pertaining to operations research and mathematical programming
90C15 Stochastic programming
90-06 Proceedings, conferences, collections, etc. pertaining to operations research and mathematical programming
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