A Robust Optimization Approach for Generating Emergency Plans with Dynamic Evolution under Uncertainty

Emergency plans are an indispensable component of emergency management, designed to effectively handle critical situations when an emergency event occurs. Due to its significance and necessity, emergency planning has drawn increasing attention in recent years. A central focus in this area is how to generate emergency plans effectively and adaptively. Numerous studies have approached this challenge from various perspectives, obtaining valuable insights and outcomes. Dynamic evolution and uncertainty are two pivotal, practical factors that emerge during emergency events and must be carefully considered in the generation of effective emergency plans. However, existing studies have not sufficiently tackled these critical aspects. To bridge this gap, this study proposes a robust optimization-based emergency plan generation method, which accounts for dynamic evolution by incorporating timeline changes, shifts in emergency situations, and updates in available resources. Additionally, it systematically integrates uncertainty from both quantitative and qualitative perspectives. Finally, an illustrative example, along with related discussions and comparisons, is provided to demonstrate the feasibility, validity, and contributions of the proposed method.