International Journal of Industrial Engineering and Management Science

International Journal of Industrial Engineering and Management Science

Evaluating The Performance Of Chicken Meat Suppliers In The Arak Metropolis Using Fuzzy TOPSIS(FT)

Document Type : Original Article

Authors
1 Department of Industrial Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran.
2 Department of Industrial Engineering, Gorgan Faculty of Engineering, Golestan University, Gorgan. Iran.
10.22034/ijiems.2024.433122.1066
Abstract
Deciding and selecting a supplier is a multi-criteria problem. This issue is strategically crucial for most organizations. The nature of such decisions is mostly complex and unstructured. Management science techniques can be useful and helpful in making decisions for these issues. The purpose of this article is to apply the Fuzzy Topsis(FTOPSIS) technique to select the best chicken meat supplier company in the Arak metropolis with maximum compliance with the set criteria. These criteria are obtained through interviews with purchasing managers. Managers in practice use these criteria in evaluating and selecting supplier companies. To collect opinions of chicken meat store managers (24 stores), instruments such as questionnaires were employed. Fuzzy Likert Scale (FLS) was utilized to convert verbal data obtained from the questionnaires.
Results: The case study indicates that three suppliers out of six suppliers have been selected as the best suppliers after using the FTOPSIS method, considering all the identified criteria. All the analyses in this study Are performed in MATLAB software. The analysis of the data collected by MATLAB software showed that Supplier No.6 (Dorsa Morgh Company) had the best performance and Supplier No. 2 (Fakhrar Company) had the worst performance in 2023.

Results: The case study indicates that three suppliers out of six suppliers have been selected as the best suppliers after using the FTOPSIS method, considering all the identified criteria. All the analyses in this study Are performed in MATLAB software.
Keywords

  • Receive Date 30 December 2023
  • Revise Date 21 May 2024
  • Accept Date 01 September 2024