Pure linguistic PROMETHEE I and II methods for heterogeneous MCGDM problems
- DOI
- 10.1080/18756891.2015.1001949How to use a DOI?
- Keywords
- PROMETHEE, linguistic preferences, linguistic difference function, linguistic preference functions, heterogeneous information, MCGDM, outranking method
- Abstract
The PROMETHEE methods basic principle is focused on a pairwise comparison of alternatives for each criterion, selecting a preference function type that often requires parameters in order to obtain a preference value. When a MCGDM problem is defined in an heterogeneous context, an adequate and common approach is to unify the involved information in linguistic values. However, for each criterion, there is a difficulty to select the specific preference function and define its parameters because they are expressed by crisp values in the unit interval, when the information involved in the problem has been unified into linguistic values. In this paper, a methodology for modeling linguistic preference functions in order to facilitate the selecting of each linguistic preference function type and the definition of its parameters is proposed, providing a more realistic definition of the criteria. Therefore, a generic linguistic preference function is proposed whose inputs and outputs are linguistic values. According to the generic linguistic preference function, six basic preference function types are extended for linguistic values. To do so, a linguistic difference function between linguistic values is defined, being its output, the input of the linguistic preference function. Furthermore, the proposed methodology is integrated in linguistic PROMETHEE I and II for heterogeneous MCGDM problems to obtain partial rankings and a full ranking of alternatives. So, the methodology provides pure linguistic PROMETHEE I and II that offer interpretability and understandability. Finally, the feasibility and applicability of pure linguistic PROMETHEE I and II are illustrated in a case study for the selection of a green supplier.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - M. Espinilla AU - N. Halouani AU - H. Chabchoub PY - 2015 DA - 2015/04/01 TI - Pure linguistic PROMETHEE I and II methods for heterogeneous MCGDM problems JO - International Journal of Computational Intelligence Systems SP - 250 EP - 264 VL - 8 IS - 2 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2015.1001949 DO - 10.1080/18756891.2015.1001949 ID - Espinilla2015 ER -