Data driven flexible supplier network of selfcare essentials during disruptions in supply chain

CHAUHAN, Ankur, KAUR, Harpreet, MANGLA, Sachin K and KAYIKCI, Yasanur (2023). Data driven flexible supplier network of selfcare essentials during disruptions in supply chain. Annals of Operations Research.

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Abstract

During disruptive events, supply chains struggle to meet the demand due to limitations posed by logistics, transportation and supply side failures. In the present study, a flexible supplier network of personal protective equipment (PPEs), such as face masks, hand sanitizers, gloves, and face shields, has been modelled using an extensive risk enabled data driven decision making for addressing disruptions in the supply chain. This paper studies various risks which exists in PPE supply chain and evaluates the total supplier risk based on them. Furthermore, the paper proposes a Multi-objective Mixed Integer Linear Program (MOMILP) to optimally select suppliers and the sustainable allocation of orders under various risks, namely disruption, delay, receivables, inventory, and capacity. The proposed MOMILP model is also extended to promptly revise the orders to other suppliers under a disruption scenario enabling an effective response resulting in minimization of stockouts. The criteria-risk matrix is developed with the help of supply chain experts from industry and academia. Conclusively, the numerical case study and its computational analysis is conducted on the PPE data received from distributors to demonstrate the applicability of the proposed model. The findings suggest that the proposed flexible MOMILP can optimally revise allocations during disruptions to drastically reduce the stockouts and minimize overall cost of procurement in the PPE supply network.

Item Type:	Article
Additional Information:	25/04/2023 author confirmed submitted before 15 October 2022.
Uncontrolled Keywords:	01 Mathematical Sciences; 08 Information and Computing Sciences; 15 Commerce, Management, Tourism and Services; Operations Research; 35 Commerce, management, tourism and services; 46 Information and computing sciences; 49 Mathematical sciences
Identification Number:	https://doi.org/10.1007/s10479-023-05298-2
SWORD Depositor:	Symplectic Elements
Depositing User:	Symplectic Elements
Date Deposited:	18 Apr 2023 11:05
Last Modified:	12 Apr 2024 01:18
URI:	https://shura.shu.ac.uk/id/eprint/31772

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