The findings suggest that the proposed flexible Multi-objective Mixed Integer Linear Program (MOMILP) can optimally revise allocations during disruptions to drastically reduce the stockouts and minimize overall cost of procurement in the PPE supply network.
Sachin Kumar Mangla, Full Professor and Director, Research Center for Digital Circular Economy for Sustainable Development Goals (DCE-SDG), Jindal Global Business School, O.P. Jindal Global University, Haryana, India.
Ankur Chauhan, Jaipuria Institute of Management, Noida, India.
Harpreet Kaur, Indian Institute of Management, Amritsar, India.
Yasanur Kayikci, Department of Engineering and Mathematics, Sheffield Hallam University, Sheffield, United Kingdom.
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.
Published in: Annals of Operations Research
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