Stochastic Programming / Edition 1

by András Prékopa

Overview

Shastic programming - the science that provides us with tools to design and control shastic systems with the aid of mathematical programming techniques - lies at the intersection of statistics and mathematical programming. The book Shastic 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.

Product Details

ISBN-13:	9780792334828
Publisher:	Springer Netherlands
Publication date:	07/31/1995
Series:	Mathematics and Its Applications , #324
Edition description:	1995
Pages:	600
Product dimensions:	6.14(w) x 9.21(h) x 0.36(d)

Table of Contents

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 Shastic 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 Shastic Programming Problems.- 13 Multi-Stage Shastic Programming Problems.- 14 Special Cases and Selected Applications.- 15 Distribution Problems.- Appendix. The Multivariate Normal Distribution.- Author Index.

Editorial Reviews

A graduate textbook that presents a comprehensive introduction to the field of stochastic programming (which provides tools to design and control stochastic systems with the aid of mathematical programming techniques) and its basic mathematical tools. While the mathematics is of a high level, the developed models offer powerful applications, demonstrated by a large number of examples. The material presented ranges from basic linear programming to algorithmic solutions of sophisticated system problems, and applications in such areas as water resources and power systems, ship manufacturing, and inventory control. Most chapters include exercises and problems. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Booknews