EconPapers    
Economics at your fingertips  
 

Introduction

Uwe Gotzes

Chapter Chapter 1 in Decision Making with Dominance Constraints in Two-Stage Stochastic Integer Programming, 2009, pp 1-12 from Springer

Abstract: Abstract This work deals with Stochastic Programming Uncertainty is a key issue in many decision problems and ignoring randomness easily leads to inferior or even infeasible decisions. In contrast to the neighboring mathematical fields, such as online or robust optimization [3, 15, 16], stochastic programming models benefit from the assumption that probability distributions governing the data are known. This underlying probabilistic model of uncertainty turns finding optimal decisions into selecting “best” random variables and evokes the need to adequately compare random variables according to their utility in the respective context.

Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-8348-9991-0_1

Ordering information: This item can be ordered from
http://www.springer.com/9783834899910

DOI: 10.1007/978-3-8348-9991-0_1

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-05-21
Handle: RePEc:spr:sprchp:978-3-8348-9991-0_1