A multi-period multi-modal stochastic supply chain model under COVID pandemic: A poultry industry case study in Mississippi

The poultry industry is one of the most important agricultural sectors, which constitutes a significant part of the per capita consumption of protein and meat. Integrating operations of poultry industry sections including production, distribution and consumption becomes vital. Although the proper poultry supply chain has been established and made plenty of benefits for a long time, the global outbreak of COVID-19 shows that operations under pandemic are still challenge for the poultry industry. In this paper, the impacts of pandemic on poultry industry is investigated by developing a multi-period multi-modal stochastic poultry supply chain. Two models are developed aiming to mitigate the negative effects of pandemic occurrence through product stocking policy. In the first model, distribution system is in accordance with a multi-component structure, while the second model allows direct connections between suppliers (farmers) and demanders (customers). In both models, poultry productions are negatively affected by COVID 19. Due to the complexity of the model, a hybrid solution approach based on Branch and Cut and Dynamic Programming is developed. To validate the performance of the proposed model and solution procedure, a case study on the broiler industry in the state of Mississippi is performed. The results show that storing poultry products in the pre-pandemic along with direct logistics during pandemic period can save the broiler supply chain cost up to 30%.