This description of stochastic dynamical optimization models is intended to exhibit some of the connections between various formulations that have appeared in the literature, and indicate some of the difficulties that must be overcome when trying to adapt solution methods that have been successfully applied to one class of problems to an apparently related but different class of problems. The emphasis is on solvable models. The authors begin with the least dynamical versions of stochastic optimization models, one- and two-stage models then consider discrete time models, and conclude with continuous time models
A wide range of problems in economics, agriculture, and natural resource management have been analyz...
Statistical procedures are developed for reducing the number of autonomous state variables in stocha...
Abstract variational theory application to continuous parameter stochastic optimization problems to ...
This book explores discrete-time dynamic optimization and provides a detailed introduction to both d...
The focus of the present volume is stochastic optimization of dynamical systems in discrete time whe...
Stochastic dynamic programming is a recursive method for solving sequential or multistage decision p...
The course covers a variety of topics in stochastic optimization. To begin with, some ap-proaches to...
Many problems that require decisions made over time can be formulated as dynamic linear programs. Co...
This text gives a comprehensive coverage of how optimization problems involving decisions and uncert...
International audienceMany stochastic dynamic programming tasks in continuous action-spaces are tack...
Multistage stochastic optimization aims at finding optimal decision strategies in situations where t...
Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult ...
This paper deals with a problem o f dynamic optimization with values o f criteria function in the s...
Stochastic optimization problems with an objective function that is additive over a finite number of...
The dissertation focuses on stochastic optimization. The first chapter proposes a typology of stocha...
A wide range of problems in economics, agriculture, and natural resource management have been analyz...
Statistical procedures are developed for reducing the number of autonomous state variables in stocha...
Abstract variational theory application to continuous parameter stochastic optimization problems to ...
This book explores discrete-time dynamic optimization and provides a detailed introduction to both d...
The focus of the present volume is stochastic optimization of dynamical systems in discrete time whe...
Stochastic dynamic programming is a recursive method for solving sequential or multistage decision p...
The course covers a variety of topics in stochastic optimization. To begin with, some ap-proaches to...
Many problems that require decisions made over time can be formulated as dynamic linear programs. Co...
This text gives a comprehensive coverage of how optimization problems involving decisions and uncert...
International audienceMany stochastic dynamic programming tasks in continuous action-spaces are tack...
Multistage stochastic optimization aims at finding optimal decision strategies in situations where t...
Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult ...
This paper deals with a problem o f dynamic optimization with values o f criteria function in the s...
Stochastic optimization problems with an objective function that is additive over a finite number of...
The dissertation focuses on stochastic optimization. The first chapter proposes a typology of stocha...
A wide range of problems in economics, agriculture, and natural resource management have been analyz...
Statistical procedures are developed for reducing the number of autonomous state variables in stocha...
Abstract variational theory application to continuous parameter stochastic optimization problems to ...