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

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

Growing Science » Uncertain Supply Chain Management » Contribution of robust optimization on handling agricultural processed products supply chain problem during Covid-19 pandemic

Journals

USCM Volumes

Volume 1 (22)
- Issue 1 (4)
- Issue 2 (6)
- Issue 3 (6)
- Issue 4 (6)

Volume 2 (32)
- Issue 1 (7)
- Issue 2 (5)
- Issue 3 (10)
- Issue 4 (10)

Volume 3 (39)
- Issue 1 (9)
- Issue 2 (13)
- Issue 3 (10)
- Issue 4 (7)

Volume 4 (31)
- Issue 1 (10)
- Issue 2 (6)
- Issue 3 (6)
- Issue 4 (9)

Volume 5 (26)
- Issue 1 (6)
- Issue 2 (6)
- Issue 3 (8)
- Issue 4 (6)

Volume 6 (25)
- Issue 1 (7)
- Issue 2 (6)
- Issue 3 (6)
- Issue 4 (6)

Volume 7 (57)
- Issue 1 (8)
- Issue 2 (19)
- Issue 3 (14)
- Issue 4 (16)

Volume 8 (82)
- Issue 1 (20)
- Issue 2 (15)
- Issue 3 (17)
- Issue 4 (30)

Volume 9 (117)
- Issue 1 (25)
- Issue 2 (26)
- Issue 3 (32)
- Issue 4 (34)

Volume 10 (150)
- Issue 1 (28)
- Issue 2 (32)
- Issue 3 (44)
- Issue 4 (46)

Volume 11 (190)
- Issue 1 (42)
- Issue 2 (45)
- Issue 3 (50)
- Issue 4 (53)

Volume 12 (244)
- Issue 1 (55)
- Issue 2 (59)
- Issue 3 (63)
- Issue 4 (67)

Volume 13 (62)
- Issue 1 (15)
- Issue 2 (15)
- Issue 3 (15)
- Issue 4 (17)

Volume 14 (15)
- Issue 1 (5)
- Issue 2 (5)
- Issue 3 (5)

Countries

Uncertain Supply Chain Management

ISSN 2291-6830 (Online) - ISSN 2291-6822 (Print) Quarterly Publication Volume 10 Issue 1 pp. 239-254 , 2022

Contribution of robust optimization on handling agricultural processed products supply chain problem during Covid-19 pandemic Pages 239-254 Download PDF

Authors: Diah Chaerani, Athaya Zahrani Irmansyah, Tomy Perdana, Nurul Gusriani

DOI: 10.5267/j.uscm.2021.9.004

Keywords: Supply Chain, Agricultural Processed Product Distribution, Robust Optimization, Covid-19 Pandemic, Local Food Hubs

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

 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.

Refrences

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.