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. 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. Front Matter....Pages i-xviii General Theory of Linear Programming....Pages 1-33 Convex Polyhedra....Pages 35-57 Special Problems and Methods....Pages 59-85 Logconcave and Quasi-Concave Measures....Pages 87-123 Moment Problems....Pages 125-178 Bounding and Approximation of Probabilities....Pages 179-217 Statistical Decisions....Pages 219-232 Static Stochastic Programming Models....Pages 233-268 Solutions of the Simple Recourse Problem....Pages 269-299 Convexity Theory of Probabilistic Constrained Problems....Pages 301-317 Programming under Probabilistic Constraint and Maximizing Probabilities under Constraints....Pages 319-371 Two-Stage Stochastic Programming Problems....Pages 373-423 Multi-Stage Stochastic Programming Problems....Pages 425-446 Special Cases and Selected Applications....Pages 447-500 Distribution Problems....Pages 501-539 Back Matter....Pages 541-599
