Stochastic Programming

András Prékopa

ISBN 10: 0792334825 / ISBN 13: 9780792334828

Editore: Springer Netherlands, Springer Netherlands, 1995

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Druck auf Anfrage Neuware - Printed after ordering - Stochastic programming - the science that provides us with tools to design and control stochastic systems with the aid of mathematical programming techniques - lies at the intersection of statistics and mathematical programming. The book Stochastic Programming is a comprehensive introduction to the field and its basic mathematical tools. While the mathematics is of a high level, the developed models offer powerful applications, as revealed by the large number of examples presented. The material ranges form basic linear programming to algorithmic solutions of sophisticated systems problems and applications in water resources and power systems, shipbuilding, inventory control, etc. Audience: Students and researchers who need to solve practical and theoretical problems in operations research, mathematics, statistics, engineering, economics, insurance, finance, biology and environmental protection.

Codice articolo 9780792334828

Dati bibliografici

• Titolo: Stochastic Programming
• Editore: Springer Netherlands, Springer Netherlands
• Data di pubblicazione: 1995
• Lingua: Inglese
• ISBN 10: 0792334825
• ISBN 13: 9780792334828
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 240 L x 161 A x 39 P (millimetri) 240 millimetri di larghezza per 161 millimetri di altezza per 39 millimetri di profonditŕ
• Peso: 1088 grammi

Descrizione articolo

Riassunto

Stochastic programming - the science that provides us with tools to design and control stochastic systems with the aid of mathematical programming techniques - lies at the intersection of statistics and mathematical programming. The book Stochastic Programming is a comprehensive introduction to the field and its basic mathematical tools. While the mathematics is of a high level, the developed models offer powerful applications, as revealed by the large number of examples presented. The material ranges form basic linear programming to algorithmic solutions of sophisticated systems problems and applications in water resources and power systems, shipbuilding, inventory control, etc.
Audience: Students and researchers who need to solve practical and theoretical problems in operations research, mathematics, statistics, engineering, economics, insurance, finance, biology and environmental protection.

Contenuti

1. General Theory of Linear Programming. 2. Convex Polyhedra. 3. Special Problems and Methods. 4. Logconcave and Quasi-Concave Measures. 5. Moment Problems. 6. Bounding and Approximation of Probabilities. 7. Statistical Decisions. 8. Static Stochastic Programming Models. 9. Solutions of the Simple Recourse Problem. 10. Convexity Theory of Probabilistic Constrained Problems. 11. Programming under Probabilistic Constraint and Maximizing Probabilities under Constraints. 12. Two-Stage Stochastic Programming Problems. 13. Multi-Stage Stochastic Programming Problems. 14. Special Cases and Selected Applications. 15. Distribution Problems. The Multivariate Normal Distribution.