Best criteria selection based PROMETHEE II to aid decision-making under 2-tuple linguistic framework: case-study of the most energy efficient region worldwide
Anjali Singh and
Anjana Gupta
International Journal of Management and Decision Making, 2020, vol. 19, issue 1, 44-65
Abstract:
In this paper, a new methodology, inspired by the PROMETHEE II method, is proposed to analyse and elucidate the decision making problems under the 2-tuple linguistic framework. The approach primarily gives prominence to decision problems with a large number of alternatives and criteria. The featuring essence of the algorithm is extraneity of the criteria weights, an imperative prerequisite for linguistic PROMETHEE II method. A case study to examine the energy efficiency of eight regions worldwide based on numerous energy efficiency indicators, as reported in World Energy Council (WEC) 8th triennial report on energy efficiency policies, is explored under the 2-tuple linguistic framework to manifest the applicability of the proposed methodology. The validity of the acquired rank of the regions is ascertained from the outlook of rank correlation coefficient. The algorithm evinces high correlation with prominent extant multi-criteria decision making (MCDM) methods to indicate the efficacy and competency of the proposed method.
Keywords: multi-criteria decision-making; MCDM; energy efficiency; 2-tuple linguistic variable; spearmen rank correlation coefficient; PROMETHEE II. (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=104210 (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:ijmdma:v:19:y:2020:i:1:p:44-65
Access Statistics for this article
More articles in International Journal of Management and Decision Making from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().