Next Article in Journal
A Framework for Automatic Building Detection from Low-Contrast Satellite Images
Next Article in Special Issue
Evaluation of the Influencing Factors on Job Satisfaction Based on Combination of PLS-SEM and F-MULTIMOORA Approach
Previous Article in Journal
Fundus Image Classification Using VGG-19 Architecture with PCA and SVD
Previous Article in Special Issue
A New Methodology for Improving Service Quality Measurement: Delphi-FUCOM-SERVQUAL Model
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Symmetry 2019, 11(1), 2; https://doi.org/10.3390/sym11010002

Probabilistic Linguistic Preference Relation-Based Decision Framework for Multi-Attribute Group Decision Making

1
School of Computing, SASTRA University, Thanjavur-613401, Tamil Nadu, India
2
Department of Mathematics, National Institute of Technology, Durgapur-713209, West Bengal, India
3
Department of General Studies, Higher College of Technology, Fujairah-4114, UAE
*
Author to whom correspondence should be addressed.
Received: 26 November 2018 / Revised: 12 December 2018 / Accepted: 17 December 2018 / Published: 20 December 2018
Full-Text   |   PDF [629 KB, uploaded 20 December 2018]   |  

Abstract

With trending competition in decision-making process, linguistic decision-making is gaining attractive attention. Previous studies on linguistic decision-making have neglected the occurring probability (relative importance) of each linguistic term which causes unreasonable ranking of objects. Further, decision-makers’ (DMs) often face difficulties in providing apt preference information for evaluation. Motivated by these challenges, in this paper, we set our proposal on probabilistic linguistic preference relation (PLPR)-based decision framework. The framework consists of two phases viz., (a) missing value entry phase and (b) ranking phase. In phase (a), the missing values of PLPR are filled using a newly proposed automatic procedure and consistency of PLPR is ensured using a consistency check and repair mechanism. Following this, in phase (b), objects are ranked using newly proposed analytic hierarchy process (AHP) method under PLPR context. The practicality of the proposal is validated by using two numerical examples viz., green supplier selection problem for healthcare and the automobile industry. Finally, the strength and weakness of the proposal are discussed by comparing with similar methods. View Full-Text
Keywords: analytic hierarchy process; consistency measure; group decision-making; probabilistic linguistic preference relation analytic hierarchy process; consistency measure; group decision-making; probabilistic linguistic preference relation
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Krishankumar, R.; Ravichandran, K.S.; Ahmed, M.I.; Kar, S.; Tyagi, S.K. Probabilistic Linguistic Preference Relation-Based Decision Framework for Multi-Attribute Group Decision Making. Symmetry 2019, 11, 2.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Symmetry EISSN 2073-8994 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top