Application of Dempster-Shafer theory in combining the experts’ opinions in DEA

Omid Yaghubi Agreh and Alireza Ghaffari-Hadigheh

Journal of the Operational Research Society, 2019, vol. 70, issue 6, 915-925

Abstract: In data envelopment analysis models, values of inputs, outputs and their slack weights are usually based on the domain experts’ opinions. While they play a key role in efficiency evaluation of decision-making units in practice, when there are more than one expert, the manager encounters with the problem of effective specification of final values. The problem may be worsen when the belief degree on the opinions is not complete and differs from one expert to the other, which consequently leads to different and sometimes conflicting analytic results. Belief function defined in Dempster–Shafer theory is a powerful tool to derive a possible solution in these circumstances. We adapt this theory to address such situations in data envelopment analysis. A linear optimisation model is devised as a new combination rule of experts’ opinions, which covers the drawbacks of some existing combination rules in the belief function theory. The methodology is visualised with simple examples. Moreover, the well-known Monte Carlo experimentation is used to test the performance of the proposed method.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/01605682.2018.1468858 (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:taf:tjorxx:v:70:y:2019:i:6:p:915-925

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjor20

DOI: 10.1080/01605682.2018.1468858

Access Statistics for this article

Journal of the Operational Research Society is currently edited by Tom Archibald

More articles in Journal of the Operational Research Society from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().