Integrating fuzzy AHP and Z-TOPSIS for supplier selection in an automotive manufacturing company

Nazihah Ahmad, Abdul Yaakob, Alexander Gegov, Maznah Mat Kasim

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Selecting the right supplier is one important process in a supply chain of a company. It will reduce procurement cost but increase stakeholders’ satisfaction. Living in the environment filled with uncertainties, while the suppliers are prescribed under multiple criteria and also the expert may not be able to evaluate the suppliers precisely, fuzzy multi-criteria decision making (MCDM) is used to handle this uncertain situation. However, the classical fuzzy MCDM assumes decision information is completely reliable. Thus, the main aim of this study is to incorporate the degree of reliability of the expert’s judgment in fuzzy environment by integrating fuzzy MCDM with Z-number. Fuzzy AHP is used to determine the weight of criteria/sub-criteria and rating the suppliers in an automotive manufacturing company, while Z-TOPSIS is used to evaluate the overall performance of suppliers. Results of the evaluation would help the purchasing manager to determine the right supplier that fulfills the company’s goal. Besides, the methodology of this study is a good guide to be implemented in other multi-criteria decision making problems.
Original languageEnglish
Title of host publicationAIP Conference Proceedings
PublisherAIP Publishing
ISBN (Print)978-0-7354-1881-3
Publication statusPublished - 21 Aug 2019
Event4th Innovation and Analytics Conference & Exhibition - Universiti Utara Malaysia, Sintok, Malaysia
Duration: 25 Mar 201928 Mar 2019


Conference4th Innovation and Analytics Conference & Exhibition
Abbreviated titleIACE 2019
Internet address


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