Extension of TODIM for decision making in fuzzy environment: a case empirical research on selection of industrial robot

Dilip Kumar Sen, Saurav Datta and Siba Sankar Mahapatra

International Journal of Services and Operations Management, 2017, vol. 26, issue 2, 238-276

Abstract: In order to facilitate decision making in robot selection problem, in this paper, an efficient fuzzy-based multi-criteria decision making (MCDM) tool has been highlighted. TODIM coupled with generalised fuzzy numbers (GFNs) set theory (fuzzy-TODIM) has been utilised here to determine the most preferable robot among all possible candidate alternatives. The results obtained thereof, have been compared to that of existing fuzzy-TOPSIS technique. We also propose a new formulation of fuzzy-TODIM (F-TODIM) by exploring the concept of similarity measure (between two fuzzy numbers) in order to compute relative gain and loss for pairs of alternatives with respect to a particular criteria. Similar ranking order of the alternative robots as obtained (in comparison with the F-TODIM formulation based on fuzzy distance measure) exhibits that fuzzy degree of similarity can fruitfully be utilised to evaluate dominance between two alternatives.

Keywords: robot selection; multicriteria decision making; MCDM; TODIM; generalised fuzzy numbers; fuzzy TOPSIS; industrial robots; fuzzy set theory; fuzzy logic; similarity measures. (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.inderscience.com/link.php?id=81492 (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:ijsoma:v:26:y:2017:i:2:p:238-276

Access Statistics for this article

More articles in International Journal of Services and Operations Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().