This text gives a comprehensive coverage of how optimization problems involving decisions and uncertainty may be handled by the methodology of Stochastic Dynamic Programming (SDP). A rapidly changing world with seemingly growing uncertainty needs a modern approach to this classic methodology. The book treats discrete, as well as continuous problems, all illustrated by relevant real world examples. The book presents a comprehensive outline of SDP from its roots during World War II until today. Much of recent research are covered, as well as parts of the authors’ own original research. Algorithms and computer techniques are added when needed. The book may serve as a supplementary text book on SDP (preferably at the graduate level) given adequ...
Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult ...
Stochastic programming is an optimization approach taking into account uncertainties in the system m...
This description of stochastic dynamical optimization models is intended to exhibit some of the con...
The course covers a variety of topics in stochastic optimization. To begin with, some ap-proaches to...
This book explores discrete-time dynamic optimization and provides a detailed introduction to both d...
2017-07-19Dynamic programming has become a common method in practice in solving optimization problem...
Stochastic methods are present in our daily lives, especially when we need to make a decision based ...
Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of a...
Title: Stochastic Dynamic Programming Problems: Theory and Applications Author: Gabriel Lendel Depar...
Abstract Stochastic Programming (SP) was first introduced by George Dantzig in the 1950’s. Since tha...
From the Preface… The preparation of this book started in 2004, when George B. Dantzig and I, follow...
Dynamic programming is a mathematical technique which provides a systematic procedure for determinin...
Sequential decision-making via dynamic programming. Unified approach to optimal control of stochasti...
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessib...
The focus of the present volume is stochastic optimization of dynamical systems in discrete time whe...
Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult ...
Stochastic programming is an optimization approach taking into account uncertainties in the system m...
This description of stochastic dynamical optimization models is intended to exhibit some of the con...
The course covers a variety of topics in stochastic optimization. To begin with, some ap-proaches to...
This book explores discrete-time dynamic optimization and provides a detailed introduction to both d...
2017-07-19Dynamic programming has become a common method in practice in solving optimization problem...
Stochastic methods are present in our daily lives, especially when we need to make a decision based ...
Introduction to Stochastic Dynamic Programming presents the basic theory and examines the scope of a...
Title: Stochastic Dynamic Programming Problems: Theory and Applications Author: Gabriel Lendel Depar...
Abstract Stochastic Programming (SP) was first introduced by George Dantzig in the 1950’s. Since tha...
From the Preface… The preparation of this book started in 2004, when George B. Dantzig and I, follow...
Dynamic programming is a mathematical technique which provides a systematic procedure for determinin...
Sequential decision-making via dynamic programming. Unified approach to optimal control of stochasti...
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessib...
The focus of the present volume is stochastic optimization of dynamical systems in discrete time whe...
Stochastic Optimization Algorithms have become essential tools in solving a wide range of difficult ...
Stochastic programming is an optimization approach taking into account uncertainties in the system m...
This description of stochastic dynamical optimization models is intended to exhibit some of the con...