Stochastic Multi-Stage Optimization: At the Crossroads between Discrete Time Stochastic Control and Stochastic Programming

Discusses the role of information in dynamic stochastic optimization problems Proposes a typology of information structures to delineate those which are numerically tractable Proposes discretization methods jointly handling the stochastic components and the information structure of tractable problems and studies convergence issues for numerically tractable information structures The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues. There is a growing need to tackle uncertainty in applications of optimization. For example the massive introduction of renewable energies in power systems challenges traditional ways to manage them. This book lays out basic and advanced tools to handle and numerically solve such problems and thereby is building a bridge between Stochastic Programming and Stochastic Control. It is intended for graduates readers and scholars in optimization or stochastic control, as well as engineers with a background in applied mathematics. Related Subjects: Continuous Optimization, Probability Theory and Stochastic Processes