Edited by Kurt Marti, Yuri Ermoliev, and Georg Pflug
©2004 by Springer-Verlag and IIASA

Summary
This volume considers optimal stochastic decision processes from the viewpoint of stochastic programming. It focuses on theoretical properties and on approximate or numerical solution techniques for time-dependent optimization problems with random parameters (multistage stochastic programs, optimal stochastic decision processes). Methods for finding approximate solutions of probabilistic and expected cost based deterministic substitute problems are presented. Besides theoretical and numerical considerations, the proceedings volume contains selected refereed papers on many practical applications to economics and engineering: risk, risk management, portfolio management, finance, insurance-matters and control of robots.

Audience
Dynamic Stochastic Optimization was written for scientists.

Key words
Dynamic Stochastic Optimization
Multistage Stochastic Programming
Stochastic Decision Processes
Economic Design under Stochastic Uncertainty
Optimal Control Problems with Random Parameters

Other recent IIASA publications

Responsible for this page: IIASA Web Team
Last updated: 24 Feb 2011