Overview

This monograph deals with theoretical fundamentals and numerical methods of optimizing nondetermined models of systems. The main body of this work is devoted to investigation and optimization of system models under incomplete information. Much consideration is given to one-, two- and multistage problems of stochastic programming, solution methods and problems of solution stability. Optimization problems with fuzzy variables and optimization problems in function spaces are investigated. Examples are given for implementation of specific models of optimization under incomplete information.The book is based on lectures delivered by the author since 1965 for undergraduates and postgraduates at St. Petersburg (Leningrad) State University.Contents: Risk and Uncertainty in the Complex SystemsChance-Constrained Stochastic ProgrammingTwo-Stage Stochastic Programming ProblemsMultistage Stochastic Programming ProblemsGame Approach to Stochastic Programming ProblemsExistence of Solution and Its Optimality in Stochastic Programming ProblemsStability of Solutions in Stochastic Programming ProblemsMethods for Solving Infinite and Semi-Infinite Programming ProblemsOptimization of Fuzzy SetsOptimization of Nonlinear Programming Problems with Nonuniquely Defined VariablesOptimization Problems in Function SpacesReadership: Applied mathematicians, engineers and researchers in electrical engineering and computer science.

Full Product Details

9781299615076

Table of Contents

Reviews

Author Information

Tab Content 6

Customer Reviews

Recent Reviews

Countries Available