ZBWM: The Z-number extension of Best Worst Method and its application for supplier development

Hamed Aboutorab, Morteza Saberi, Mehdi Rajabi Asadabadi, Omar Hussain, Elizabeth Chang

Research output: Contribution to journalArticlepeer-review

273 Citations (Scopus)

Abstract

Best Worst Method (BWM) has recently been proposed as a method for Multi Criteria Decision Making (MCDM). Studies show that BWM compared with other methods such as Analytic Hierarchy Process (AHP), leads to lower inconsistency of the results while reducing the number of required pairwise comparisons. MCDM methods such as BWM require accurate information. However, it often happens in practice that a level of uncertainty accompanies the information. The main aim of this paper is to address this problem and provide an integration of BWM and Z-numbers, namely ZBWM. Providing BWM with Z-numbers enables the BWM method to handle the uncertainty of information of a multi-criteria decision. Additionally, the capabilities of the proposed method in the process of utilizing the linguistic information dealing with big data are highlighted. The proposed method is examined to address a supplier development problem. By experimental results, we show that ZBWM results lower inconsistency when compared with BWM. A Z-number contains subjectivity in its fuzzy part, which can be addressed in future applications of ZBWM.

Original languageEnglish
Pages (from-to)115-125
Number of pages11
JournalExpert Systems with Applications
Volume107
DOIs
Publication statusPublished - 1 Oct 2018
Externally publishedYes

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