Stochastic Programming: Theory, Applications and Impacts

This book is concerned with fostering theoretical issues on stochastic programming and discussing how it can solve real life problems.

The book presents applications which solve the optimization of concrete problems in electricity markets, market equilibria, resource markets and environments. Each chapter presents a survey on the main results concerned with its contents, and discusses their impact by illustrating how they are applicable in real life. The authors use concrete, real life problems and simulation-motivated experiments for illustrating the behavior of the stochastic models discussed.
The target audience for this title is graduate students or researchers in optimization, approximation, statistics, operations research and computing, as well as professionals dealing with applications where uncertainty may be modeled by using stochastic optimization and academics.

The contributors are well-known specialists in stochastic programming

Series:
Mathematics Research Developments

Table of Contents

Chapter 1 Random Approximations in Stochastic Programming: A Survey
Chapter 2 Approximation and Estimation of the Approximation Error in Stochastic Programing Programs
Chapter 3 Probabilistic Linear Programming Problem with Cauchy Distributed Random Variables
Chapter 4 Stochastic Modeling of Imperfect Markets
Chapter 5 Optimizing Derivatives through Stochastic Programming
Chapter 6 A Guide for the Use of the Stochastic Programming References Reported in the Contributions of this Book