Stochastic Programming
Published on 15. December 2010
Book
Paperback/Softback
XVIII, 600 pages
978-90-481-4552-2 (ISBN)
Description
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.
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.
More details
Series
Edition
1st ed. Softcover of orig. ed. 1995
Language
English
Place of publication
Dordrecht
Netherlands
Target group
Professional and scholarly
Research
Illustrations
XVIII, 600 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 34 mm
Weight
925 gr
ISBN-13
978-90-481-4552-2 (9789048145522)
DOI
10.1007/978-94-017-3087-7
Schweitzer Classification
Other editions
Additional editions
András Prékopa
Stochastic Programming
Book
07/1995
Kluwer Academic Publishers
€246.09
Shipment within 15-20 days
Person
Prof. András Prékopa is a Professor at Rutgers University in the Department of Statistics.
Prof. János Mayer is a Professor at University of Zurich in the Department of Business Adminstration.
Prof. Beáta Strazicky is currently retired but was a Professor at Szent István University.
Prof. István Deák is a Professor at Corvinus University of Budapest in the Department of Computer Science.
János Hoffer works at Allianz Hungária Insurance Company in the IT Quality Assurance Section.
Ágoston Németh works in Ex-Lh Ltd.
Béla Potecz is retired but previously worked for MAVIR Hungarian Independent Transmission Operator Company Ltd.
Content
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.