Stochastic Programming

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...

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Bibliographic Details
Main Author: Prékopa, András
Format: eBook
Language:English
Published: Dordrecht Springer Netherlands 1995, 1995
Edition:1st ed. 1995
Series:Mathematics and Its Applications
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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505 0 |a 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 -- Appendix. The Multivariate Normal Distribution -- Author Index 
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653 |a Optimization 
653 |a Management science 
653 |a Probability Theory 
653 |a Mathematical optimization 
653 |a Probabilities 
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520 |a 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