EconPapers    
Economics at your fingertips  
 

Pareto optimal solution for multiobjective stochastic linear programming problems with partial uncertainty

Abdulqader Othman Hamadameen and Nasruddin Hassan

International Journal of Mathematics in Operational Research, 2018, vol. 12, issue 2, 139-166

Abstract: A study on multiobjective stochastic linear programming (MSLP) problems with partial information on probability distribution is conducted. A method is proposed to utilise the concept of dominated solution for the multiobjective linear programming (MLP) problems, and find a pareto optimal solution (POS) without converting the MLP problem into its unique linear programming (LP) problem. An algorithm is proposed along with a numerical example which illustrated the practicability of the proposed algorithm. Comparison of results with existing methods shows the efficiency of the proposed method based on the analysis of results performed.

Keywords: dominated solution; fuzzy transformation; MSLP problems; pareto optimal solution; POS; stochastic transformation. (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=89675 (text/html)
Access to full text is restricted to subscribers.

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:ids:ijmore:v:12:y:2018:i:2:p:139-166

Access Statistics for this article

More articles in International Journal of Mathematics in Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijmore:v:12:y:2018:i:2:p:139-166