This paper discusses an optimization model for handling the impact of the COVID-19 pandemic based on food supply network through regional food hubs (RFHs) under uncertainty. To this end, uncertainty is assumed in the demand and production data. During the Pandemic COVID-19 period, uncertainty has increased and the food supply chain system has changed. Thus, a new configuration of the food supply network requires analysis. In this paper, the concept of RFH is introduced to connect producers in rural areas and customers in urban areas. This paper determines the location and capacity of RFHs, the food supply network, the sum of maximum food supplies, and minimum logistics cost. This is done via a Multi-Objective Many-to-Many Location-Routing Problem model. Furthermore, since the conditions of the COVID-19 pandemic is uncertain, robust optimization is employed to handle uncertainties. During the current pandemic, red zones are defined to indicate the severity of the pandemic in a region. In this paper, the numerical experiment is considered for three scenarios: when a region is in largescale social distancing, partial social distancing, or normal conditions. This social distancing situation is based on the defined red zones. The optimal food supply network is obtained for the three scenarios and the best scenario among the three is identified.

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Horticulture is one of the important components of Indonesia’s economy that come from the agricultural sector. However, many challenges are encountered in the development of horticultural supply chains (HSCs) in Indonesia. One of them is the lack of production planning that suits the market demand. This results in inefficiency, high food losses and price fluctuation. HSCs systems are complex, especially in developing countries like Indonesia in which many smallholders are involved. Concerning this situation, ICT-based approaches have been widely proposed to integrate planning along supply chains. One of the approaches is a symbiotic simulation that enables a close association between the real system and simulation system. Symbiotic simulation is designed to support decision-makers to plan their activities using the real/near real-time data generated by the real systems as the inputs. However, how this system model can be used in HSC systems involving many smallholders is still a question. This paper proposes a framework to design decision support symbiotic simulations for HSC systems involving smallholders. The framework is designed based on the literature study on symbiotic simulation and agricultural supply chains in developing countries. In this framework, four activities in the HSCs are considered: 1) production; 2) post-production; 3) logistics, and 4) market. This framework can be used by farmer organisations or agricultural companies that have partnerships with smallholders to plan their activities along their supply chains.