G-resilient multi-tier supplier selection and order allocation in food industry: a hybrid methodology

Ahmed Mohammed*, Chunguang Bai*, Nabil Channouf, Teejan Al Ahmed, Shaymaa Maher Mohamed

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


In the post epidemic era, food industry associations need to build a green and resilient (G-resilient) supply chains network through supplier selection and order allocation (SS/OA) decisions to avoid unexpected disruption risks and meet uncertain demand and cost for green food. This paper proposes a hybrid methodology using fuzzy multi-objective mixed integer linear programming model (FMOMILPM) to solve G-resilient multi-tier SS/OA problem within the uncertain demand and cost environment in food industry. We first proposed a G-resilient multi-criteria framework that consists of traditional, green and resilience pillars as well as their criteria for evaluating multi-tier suppliers. Second, FMOMILPM is developed based on the fuzzy evaluation of group decision makers and the uncertain demand and cost to handle the G-resilient multi-tier SS/OA problem towards minimizing cost and transportation time of orders and maximizing purchasing value of G-resilient. The LP-metrics and ϵ-constraint methods are employed to obtain a set of Pareto solutions out of the FMOMILPM, and then the final Pareto solution is determined by TOPSIS. The applicability of the proposed methodology is validated by a real case study in the UK halal food industry.

Original languageEnglish
Article number2195055
JournalInternational Journal of Systems Science: Operations and Logistics
Issue number1
Publication statusPublished - Apr 17 2023


  • G-resilient
  • Multi-tier
  • food industry
  • fuzzy multi-objective optimisation
  • supplier
  • uncertain demand

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Management Science and Operations Research
  • Information Systems and Management

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