The COVID-19 pandemic exposed the vulnerabilities of global supply chains (SCs) and highlighted the need for more resilient and viable SCs. Panic-buying, in particular, has been a major challenge for SCs as it can create sudden surges in demand that are difficult to anticipate and manage. However, the literature lacks viable SC models and strategies to address panic-buying related challenges. As such, this research aims to identify and model viable recovery strategies to increase SC’s agility, resilience, and survivability and reduce panic-buying’s impact during a large-scale disruption in critical SCs. This study contributes by developing an integrated agent-based modeling (ABM) and optimisation method to simulate the behaviour of SCs under different scenarios and evaluating the effectiveness of four proposed strategies and three recovery plans. The findings reveal that increasing production at decentralised manufacturing facilities can be achieved by increasing order frequency to multiple suppliers and by partnering with third-party transporters, which can mitigate the effects of panic-buying. This results in higher output and availability of essential goods in the market, significantly managing panic-buying related challenges. Lastly, the study recommends practical solutions for businesses to enhance their SCs’ responsiveness to sudden demand surges from panic-buying.