The threat of COVID-19, though significantly reduced, persists. Additionally, the ongoing uncertainty regarding the nature of potential future viral outbreaks underscores the increased importance of preventive measures. High-density and high-risk facilities, such as hospitals and apartments buildings, face significant threats. Traditional virus simulations in the past required extensive time and specialized software. However, in this study, we conducted simulations using a diverse set of heuristic algorithms based on different concepts. The experimental results indicate that heuristic algorithms not only significantly reduce overall simulation runtime—with the Crow Search Algorithm (CSA) achieving the shortest runtime in this experiment at 39.3 s—but also show a substantial deviation from traditional simulations like Computational Fluid Dynamics (CFD), which often took hours. This research not only expands the application of algorithms but also provides essential insights for management personnel in preparing for virus transmission prevention.