EconPapers    
Economics at your fingertips  
 

Viable-sustainable supplier selection and order allocation problem considering Industry 5.0 pillars under mixed uncertainty

Zeinab Asadi, Hassanali Aghajani, Mohammad Valipour Khatir and Erfan Babaee Tirkolaee

International Journal of Production Research, 2025, vol. 63, issue 20, 7591-7616

Abstract: This work addresses the Supplier Selection and Order Allocation Problem (SSOAP) with two important evolving concepts namely viability and Industry 5.0 (I5.0) wherein sustainability plays a vital role. For this purpose, an efficient decision-making model is developed which is based on Multiple-Criteria Decision-Making (MCDM) techniques. First of all, the suppliers’ scores are measured according to the viability and I5.0 dimensions. To do so, two novel decision-making approaches of Stochastic Fuzzy Best-Worst Method (SFBWM) and Stochastic Fuzzy Technique for Order Preference by Similarity to Ideal Solution (SFTOPSIS) are developed. Then, a multi-objective mathematical model (MOMM) is proposed to choose the most appropriate suppliers and specify the number of orders in which all dimensions of the viability and I5.0 concepts are incorporated. In the next step, a Robust Stochastic-Possibilistic (RSP) technique is employed to treat the mixed uncertainty. Finally, the MOMM is treated with the help of a novel improved Goal Programming (GP) approach; i.e. Lexicographic Chebyshev Revised Multi-Choice Goal Programming (LCRMCGP). A real healthcare system is then investigated as the case study problem to represent the applicability, validity, and performance of the developed model, and eventually, render useful managerial and decision aids.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2025.2502848 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:63:y:2025:i:20:p:7591-7616

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2025.2502848

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-11-05
Handle: RePEc:taf:tprsxx:v:63:y:2025:i:20:p:7591-7616