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Towards a sustainable assessment of suppliers: an integrated fuzzy TOPSIS-possibilistic multi-objective approach

  • A. MohammedEmail author
S.I.: MCDM 2017
  • 98 Downloads

Abstract

In spite of the increasing awareness apparent in the previous studies regarding the evaluation suppliers considering sustainability aspects, there are limitations on the incorporation of sustainable performance in terms of traditional, green and social aspects in supplier selection and order allocation. This paper presents the development of an integrated fuzzy TOPSIS-possibilistic multi objectives model to (1) solve a two-stage sustainable supplier selection problem; and (2) allocate the optimal flow of products quantity that should be ordered from suppliers towards the minimization of expected costs, environmental impact and travel time and maximization of social impact. Suppliers’ sustainable performance was based on traditional, green and social criteria, and quantified by using fuzzy TOPSIS and then integrated into the possibilistic multi objective model. The latter helps decision makers in having an order allocation plan that considers sustainability aspect. Furthermore, the multi-objective optimization model was re-developed as a possibilistic multi-objective optimization model (PMOOM) to handle the dynamic nature in some of the input data. Next, the LP-metrics method was employed to derive Pareto solutions out of the PMOOM. The quality of the obtained Pareto solutions was evaluated using the global criterion approach aiming to help decision makers in selecting the final Pareto solution. The applicability of the developed integrated fuzzy TOPSIS-possibilistic multi-objective approach was proven with sensitivity analysis on a case study of a meat supply chain.

Keywords

Sustainability Supplier evaluation and selection Meat supply chain TOPSIS Multi-objective optimization 

Notes

Acknowledgements

The author acknowledges the financial support from the European Regional Development Fund through the Welsh Government for ASTUTE 2020 (Advanced Sustainable Manufacturing Technologies) to facilitate this work. The author would like to thank the anonymous referees whose thorough reviews and insightful comments made a valuable contribution to this article.

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Authors and Affiliations

  1. 1.Department of Operations Management and Business Statistics, College of Economics and Political ScienceSultan Qaboos UniversityMuscatOman
  2. 2.Nineveh Telecommunication DirectorateIraqi Ministry of CommunicationsMosulIraq

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