Challenges in Stochastic Programming
Abstract
Remarkable progress has been made in the development of algorithmic procedures and the availability of software for stochastic programming problems. However, some fundamental questions have remained unexplored. This paper identifies the more challenging open questions in the field of stochastic programming. Some are purely technical in nature, but many also go to the foundations of designing models for decision making under uncertainty.
KEYWORDS: stochastic programming, decisions under uncertainty, chance-constraints, probabilistic constraints, distribution problem, Markowitz portfolio model
KEYWORDS: stochastic programming, decisions under uncertainty, chance-constraints, probabilistic constraints, distribution problem, Markowitz portfolio model