On the safe side of stochastic programming: bounds and approximations

On the safe side of stochastic programming: bounds and approximations

There will always be stochastic programs that are too large or complex to be solved in their basic form. In this article, we review, discuss, and compare different ways such stochastic programs can be handled using bounds and approximations, all based on manipulations of the random variables. We are...

Full description

Saved in:
Bibliographic Details
Published in:International transactions in operational research Vol. 30; no. 6; pp. 3201 - 3237
Main Authors: Narum, Benjamin S., Maggioni, Francesca, Wallace, Stein W.
Format: Journal Article
Language:English
Published: Oxford Blackwell Publishing Ltd 01-11-2023
Subjects:
Approximation
bounds
distribution approximation
function approximation
Operations research
Random variables
Stochastic models
Stochastic programming
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:There will always be stochastic programs that are too large or complex to be solved in their basic form. In this article, we review, discuss, and compare different ways such stochastic programs can be handled using bounds and approximations, all based on manipulations of the random variables. We are particularly interested in how methods based on different underlying ideas can be combined or possibly are the same.
ISSN:0969-6016
1475-3995
DOI:10.1111/itor.13317