Contribution of robust optimization on handling agricultural processed products supply chain problem during Covid-19 pandemic

Chaerani, D.; Irmansyah, A.; Perdana, T.; Gusriani, N.

Abstract: This research aims to show how decision sciences can make a significant contribution on handling the supply chain problem during Covid-19 Pandemic. The paper discusses how robust optimization handles uncertain demand in agricultural processed products supply chain problems within two scenarios during the pandemic situation, i.e., the large-scale social distancing and partial social distancing. The study assumes that demand and production capacity are uncertain during a pandemic situation. Robust counterpart methodology is employed to obtain the robust optimal solution. To this end, the uncertain data is assumed to lie within a polyhedral uncertainty set. The result shows that the robust counterpart model is a computationally tractable through linear programming problem. Numerical experiment is presented for the Bandung area with a case on sugar and cooking oil that is the most influential agricultural processed products besides the main staple food of the Indonesian people, rice.

How to cite this paper

        APA: Chaerani, D., Irmansyah, A., Perdana, T & Gusriani, N. (2022). Contribution of robust optimization on handling agricultural processed products supply chain problem during Covid-19 pandemic. Uncertain Supply Chain Management, 10(1), 239-254.
    

        Chicago/Turabian: Chaerani, D., Irmansyah, A., Perdana, T & Gusriani, N. 2022. "Contribution of robust optimization on handling agricultural processed products supply chain problem during Covid-19 pandemic." Uncertain Supply Chain Management 10, no. 1 (2022): 239-254.
    

        AMA: Chaerani, D., Irmansyah, A., Perdana, T & Gusriani, N. Contribution of robust optimization on handling agricultural processed products supply chain problem during Covid-19 pandemic. Uncertain Supply Chain Management. 2022;10(1):239-254.
    

References

Allen, D. W. (2021). Covid Lockdown Cost/Benefits: Critical Assessment of the Literature. Department of Economics, Simon Fraser University, Burnaby, Canada.
Andriani, H. (2020). Effectiveness of Large-Scale Social Restrictions (PSBB) toward the New Normal Era during COVID-19 Outbreak: a Mini Policy Review. Journal Of Indonesian Health Policy And Administration, 5(2), 61-65.
Ben-Tal, A., Ghaoui, L., & Nemirovski, A. (2009). Robust Optimization: Princeton Series. New Jersey: Princeton University Press.
Ben-Tal, A., & Nemirovski, A. (2002). Robust Optimization-Methodology and Applications. Mathematical Programming, B, 92, 453-480.
Li, C. (2016). The Robust Optimization in Centralized Supply Chain. Science Journal of Business and Management, 4(2), 61-66.
Covid-19 Information Center (Pusicov) Bandung. (2021). 10 Highest Active Confirmation Districts, accessed on 1 April 2021.
Delkhosh, F., & Sadjadi, S. F. (2019). A robust optimization model for biofuel supply chain under demand uncertainty. International Journal of Energy and Environmental Engineering, 11, 229-245.
Food Price Information Forum. (2021). West Java Inflation Control Coordination Forum, accessed on 28 Maret 2021.
Gorissen, B. L., Yanikoglu, I., & Hertog, D. D. (2015). A Practical Guide to Robust Optimization. Elsevier, 53, 124-137.
Irawan, A. and Alamsyah, H. (2021). The Covid-19’s Economic Crisis and Its Solutions: A Literature Review. Etikomi, 20(10), 77-92.
Lu, H., Stratton, C. W., & Tang, Y. (2020). Outbreak of Pneumonia of Unknown Etiology in Wuhan, China: The Mystery and the Miracle. Jurnal of Medical Virology, 92, 401-402.
Matson, J., Sullins, M., & Cook, C. (2013). The Role of Food Hubs in Local Food Marketing. USDA Rural Development.
Mehta, S., Saxena, T., & Purohit, N. (2020). The New Consumer Behaviour Paradigm amid COVID-19: Permanent or Transient?. Journal of Health Management, 22(2).
Muhyiddin, & Nugroho, H. (2021). A Year of Covid-19: A Long Road to Recovery and Acceleration of Indonesia’s Development, Jurnal Perencanaan Pembangunan, 5(1), 1-19.
Pishvaee, M. S., Rabbani, M., & Torabi, S. A. (2011). A robust optimization approach to closed-loop supply chain network design under uncertainty. Applied Mathematical Modelling, 35(2), 637-649.
Perdana, T., Chaerani, D., Achmad, A. L. H., & Hermiatin, F. R. (2020). Scenarios for handling the impact of COVID-19 based on food supply network through regional food hubs under uncertainty. Heliyon, 6(10), e05128.
Sari, N. N., Yuliana, D., Hervidea, R., & Agata, A. (2020). Health Protocol of Covid-19: as A Prevention of Covid-19 in the Work Area of Office Employees in Bandar Lampung. Jurnal Peduli Masyarakat, 2(4), 173-180.
Worldometers: Covid-19 Coronavirus Pandemic, https://www.worldometers.info/coronavirus/, accessed on 20 June 2021.
Yanikoglu, I., Gorissen, B. L., & Hertog, D. (2018). Adjustable Robust Optimization–A Survey and Tutorial. European Journal of Operational Research, 277(3), 799-813.

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