Issue |
RAIRO-Oper. Res.
Volume 55, Number 5, September-October 2021
|
|
---|---|---|
Page(s) | 2827 - 2860 | |
DOI | https://doi.org/10.1051/ro/2021123 | |
Published online | 20 September 2021 |
Designing a disruption-aware supply chain network considering precautionary and contingency strategies: a real-life case study
Department of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
* Corresponding author: ghousi@iust.ac.ir
Received:
6
April
2021
Accepted:
11
August
2021
Due to the high risk in the business environment, supply chains must adopt a tailored mechanism to deal with disruptions. This research proposes a multi-objective formulation to design a robust and resilient forward supply chain under multiple disruptions and uncertainty. The mentioned objective functions include minimizing the total cost, environmental impacts, and the network non-resiliency associated with the supply chain simultaneously countered using an augmented ε-constraint method. A Mulvey robust optimization approach is also utilized to deal with uncertainty. Ultimately, the developed model is validated based on three datasets associated with a case study of the steel industry. The results indicate that preventive and mitigation resilience strategies have significantly promoted the supply chain’s capabilities to deal with disruptions. Controlling network resiliency via non-resiliency measures has also created a risk-aware and robust structure in the incidence of disturbances. Numerical results reveal that multiple sourcing, lateral transshipment, and fortification of facilities will lead to the greatest cost-efficiency in the case study. Observations also indicate that the fortified supply chain will be highly economically viable in the long run due to the reduction of costs resulting from lost sales, unnecessary inventory holding, and the company’s credit risk.
Mathematics Subject Classification: 90B06
Key words: Resilient system / network non-resiliency / robust optimization / disruption / operational risk
© The authors. Published by EDP Sciences, ROADEF, SMAI 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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