Stochastic Programming, Modeling and Theory. Lecture 1

В данном курсе планируется рассмотреть следующие темы:
–Modeling and basic properties
–Two stage stochastic programming
–Decision rules
–Concept of nonanticipativity
–Dualization of the nonanticipativity constraints
–Multistage stochastic programming
–Dynamic programming equations
–Monte Carlo sampling methods
–Sample size estimates (Large Deviations type bounds)
–Stochastic Approximation (SA) approach
–Complexity of multistage stochastic programming
–Risk-averse approach
–Time consistency
Литература:
Lectures on Stochastic Programming: Modeling and Theory (MPS-SIAM Series on Optimization)
Alexander Shapiro, Darinka Dentcheva, Andrzej Ruszczynski