Designing Food Supply Chain Strategy During COVID-19 Pandemic Using an Integrated Agent-Based Modelling and Robust Optimization

Abstract

Coronavirus disease (COVID-19) has spread for over a year and affected many aspects, including food supply chain. One of the impacts of COVID-19 in food supply chain is the reduction of food production capacity. It is necessary to develop the optimum food supply chain strategy by determining the optimum food hub location and food network to maintain the food security which robust against disruptions and uncertainties. In this study, Robust Optimization (RO) is applied to handle the uncertainties. Nevertheless, the actual uncertain data might be hard to be collected or even unavailable at the moment. Therefore, an innovative framework is proposed to integrate RO with Agent-Based Modelling (ABM). ABM is used to simulate the upstream actor of food supply chain and predict the uncertain food production capacity, which later handled by RO. Particularly, this study focused on rice supply chain. Result shows that the framework is able to handle the uncertain rice supply chain problem, in which the actual uncertain data might be unavailable, and give the robust optimum food hub location and food network. The food hub location and food network are obtained by solving the Robust Counterpart (RC) model with respect to the uncertainty set obtained from the ABM simulation result.Funding Information: This research is funded by The Indonesian Ministry of Research and Technology/National Research and Innova tion Agency through contract number 1827/UN6.3.1/LT/2020 entitled “Coordination Model of Food Supply Chain Management in COVID-19 Pandemic“Declaration of Interests: The authors declare no conflict of interest.