A compromise solution method for the multiobjective minimum risk problem
Fatima Bellahcene () and
Philippe Marthon ()
Additional contact information
Fatima Bellahcene: Mouloud Mammeri University
Philippe Marthon: ENSEEIHT Informatique
Operational Research, 2021, vol. 21, issue 3, No 19, 1913-1926
Abstract:
Abstract We develop an approach which enables the decision maker to search for a compromise solution to a multiobjective stochastic linear programming (MOSLP) problem where the objective functions depend on parameters which are continuous random variables with normal multivariate distributions. The minimum-risk criterion is used to transform the MOSLP problem into its corresponding deterministic equivalent which in turn is reduced to a Chebyshev problem. An algorithm based on the combined use of the bisection method and the probabilities of achieving goals is developed to obtain the optimal or epsilon optimal solution of this specific problem. An illustrated example is included in this paper to clarify the developed theory.
Keywords: Multiobjective programming; Stochastic programming; Nonlinear programming; Minimum-risk criterion (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s12351-019-00493-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:operea:v:21:y:2021:i:3:d:10.1007_s12351-019-00493-1
Ordering information: This journal article can be ordered from
https://www.springer ... search/journal/12351
DOI: 10.1007/s12351-019-00493-1
Access Statistics for this article
Operational Research is currently edited by Nikolaos F. Matsatsinis, John Psarras and Constantin Zopounidis
More articles in Operational Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().