TY - JOUR
T1 - G-resilient multi-tier supplier selection and order allocation in food industry
T2 - a hybrid methodology
AU - Mohammed, Ahmed
AU - Bai, Chunguang
AU - Channouf, Nabil
AU - Ahmed, Teejan Al
AU - Mohamed, Shaymaa Maher
N1 - Funding Information:
This work is supported by the National Natural Science Foundation of China Project (71772032). This Research Project received Funding from the Ministry of Higher Education, Research and Innovation of the Sultanate of Oman, under Commissioned Research Program, Contract NO. 01/12/2023-31/08/2025, 01/12/2023-31/01/2025, 01/12/2021-31/07/2023, and 01/12/2021-30/11/2022.
Publisher Copyright:
© 2023 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - food industry
KW - fuzzy multi-objective optimisation
KW - G-resilient
KW - Multi-tier
KW - supplier
KW - uncertain demand
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U2 - 10.1080/23302674.2023.2195055
DO - 10.1080/23302674.2023.2195055
M3 - Article
AN - SCOPUS:85153050448
SN - 2330-2674
VL - 10
JO - International Journal of Systems Science: Operations and Logistics
JF - International Journal of Systems Science: Operations and Logistics
IS - 1
M1 - 2195055
ER -