Development of Subcontractor Selection Models Using Fuzzy and AHP Methods in the Apparel Industry Supply Chain

• Autorzy: Lahdhiri Mourad , Babay Amel , Jmali Mohamed

Identyfikatory

DOI

10.2478/aut-2020-0057

• Języki publikacji: EN

Abstrakty

EN

The subcontractor selection decision is inherently a multicriterion problem. It is a decision of strategic importance for companies. The nature of this decision is usually complex and unstructured. Management science techniques might be helpful tools for solving these kinds of decision-making problems. In this research, the fuzzy logic method and the analytic hierarchy process were applied for the selection of suitable subcontractors in an apparel supply chain. In general, many factors, such as quality level, price offer, and delivery delay, were considered to determine the most suitable and reliable subcontractors that fit the company's strategy. This survey is carried out using the database of an apparel company manufacturing denim products.

Słowa kluczowe

EN

fuzzy model; analytic hierarchy process; apparel industry; supply chain

PL

rozmyty model; proces hierarchii analitycznej; przemysł odzieżowy; łańcuch dostaw

• Wydawca: Lodz University of Technology, Faculty of Material Technologies and Textile Design
• Czasopismo: Autex Research Journal
• Rocznik: 2021
• Tom: Vol. 21, no. 4
• Strony: 413--427
• Opis fizyczny: Bibliogr. 21 poz.

Twórcy

autor

Lahdhiri Mourad

• Laboratory of Textile Engineering (LGtex), ISET Ksar Hellel, University of Monastir, Tunisia
• National Engineering School, University of Monastir, Monastir, Tunisia

autor

Babay Amel

• Laboratory of Textile Engineering (LGtex), ISET Ksar Hellel, University of Monastir, Tunisia

autor

Jmali Mohamed

• Laboratory of Textile Engineering (LGtex), ISET Ksar Hellel, University of Monastir, Tunisia

Bibliografia

• [1] Chen-Tung, C., Lin, C.-T., Huang, S.-F. (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. International Journal Production Economics, 102, 289–301.
• [2] Bayrak, M. Y., Çelebi, N., Taşkin, H. (2007). A fuzzy approach method for supplier selection. Production Planning & Control, 18, 54–63.
• [3] Maurizio, B., Alberto, P. (2010). From traditional purchasing to supplier management: A fuzzy logic based approach to supplier selection. International Journal of Logistics Research and Applications: A Leading Journal of Supply Chain Management, 5(3), 235–255.
• [4] Felix, T. S., Kumar, N., Tiwari, M. K., Lau, H. C. W., Choy, K. L. (2008). Global supplier selection: a fuzzy-AHP approach. International Journal of Production Research, 46(14), 3825–3857.
• [5] Sharon, M. O. (2009). Development of a supplier selection model using fuzzy logic. Supply Chain Management: An International Journal, 14/4, 314–327.
• [6] Devika, K. A. (2013). Integrated fuzzy multi criteria decision making method and multiobjective programming approach for supplier selection and order allocation in a green supply chain. Journal of Cleaner Production, 47, 355–367.
• [7] Michał, K. The selection of construction sub contractors using the fuzzy sets theory, Warsaw University of Technology, Faculty of Civil Engineering, Institute of Building Engineering, The Division of Production Engineering and Construction Management, Al. ArmiiLudowej 16, 00-637 Warsaw, Poland.
• [8] Min-Yuan, C. (2011). Evaluating subcontractor performance using evolutionary fuzzy hybrid neural network. International Journal of Project Management, 29(3), 349–356.
• [9] Okoroh, M. I., Torrance, V. (1999). A model for subcontractor selection in refurbishment projects. Construction Management and Economics, 17, 315–327.
• [10] Kumar, M., Vrat, P., Shankar, R. (2004). A fuzzy goal programming approach for vendor selection problem in a supply chain. Computers & Industrial Engineering, 46(1), 69–85.
• [11] Kabbari, M., et al. (2015). Predicting the hydrophobic nature of knitted fabric using fuzzy logic modeling. International Journal of Applied Research on Textile, 3, 58–68.
• [12] Mouna, G. et al. (2017). Ann and fuzzy techniques for modeling bagging behaviors of denim fabrics as function of frictional properties. International Journal of Applied Research on Textile, 2, 36–55.
• [13] Charles, A. W., John, R. (1993). A multiobjective approach to vendor selection. European Journal of Operational Research, 68(2), 173–184.
• [14] William, R. S. (1987). Supplier selection strategies. Journal of Purchasing and Materials Management, 23(2), 7–12.
• [15] Lisa, M. (1990). The supplier selection decision in strategic partenrship. Journal of Purchasing and Materials Management, 26(4), 8–14.
• [16] Roodhooft, J., Konings, J. (1997). Vendor selection and evaluation: An activity based costing approach. European Journal of Operational Research, 96, 97–102.
• [17] Hinkle, C. L., Robinson, P. J., Green, P. E. (1969). Vendor evaluation using cluster analysis. Journal of Purchasing, 5(3), 49–58.
• [18] Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.
• [19] Lotfi, B. (1999). Contribution to the control of the asynchronous machine, use of fuzzy logic, neural networks and genetic algorithms. Doctoral thesis, Université de Henri Poincaré, Nancy-I.
• [20] Thomas L. S., Kirti, P. (2008). Group decision making: Drawing out and reconciling differences. Pittsburgh, Pennsylvania: RWS Publications.
• [21] Saracoglu, B. O. (2013). Selecting industrial investment locations in master plans of countries. European Journal of Industrial Engineering, 4, 416–441.

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).