This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Analysis and Comparisons of some Solution Concepts for Stochastic Programming Problems

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
R. Caballero (Department of Applied Economics (Mathematics), University of Málaga, Spain.)
E. Cerdá (Department of Foundations of Economic Analysis, University Complutense of Madrid, Spain.)
M. Muñoz (Department of Applied Economics (Mathematics), University of Málaga, Spain.)
L. Rey (Department of Applied Economics (Mathematics), University of Málaga, Spain.)

Additional information is available for the following registered author(s):

Abstract

The aim of this study is to analyse the resolution of Stochastic Programming Problems in which the objective function depends on parameters which are continuous random variables with a known distribution probability. In the literature on these questions different solution concepts have been defined for problems of these characteristics. These concepts are obtained by applying a transformation criterion to the stochastic objective which contains a statistical feature of the objective, implying that for the same stochastic problem there are different optimal solutions available which, in principle, are not comparable. Our study analyses and establishes some relations between these solution concepts.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://eprints.ucm.es/7677/
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales in its series Documentos del Instituto Complutense de Análisis Económico with number 0218.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: 2002
Date of revision:
Handle: RePEc:ucm:doicae:0218

Contact details of provider:
Phone: 913942602
Email:
Web page: http://www.ucm.es/info/cee/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: ().

Related research
Keywords:

Other versions of this item:

This paper has been announced in the following NEP Reports: References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. Kall, P., 1982. "Stochastic programming," European Journal of Operational Research, Elsevier, vol. 10(2), pages 125-130, June. [Downloadable!] (restricted)
  2. Leclercq, J. -P., 1982. "Stochastic programming: An interactive multicriteria approach," European Journal of Operational Research, Elsevier, vol. 10(1), pages 33-41, May. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Emilio Cerdá & Julio Moreno Lorente, 2009. "Chance Constrained Programming with one Discrete Random Variable in Each Constraint," Working Papers 2009-05, FEDEA. [Downloadable!]
Statistics
Access and download statistics

Did you know? About 2700 working paper series are listed on RePEc.

This page was last updated on 2009-12-13.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.