Fairness-Driven Multi-Objective Optimization for Evacuation Planning in Natural Disasters

In the context of natural disasters such as earthquakes and tsunamis, efficient and equitable evacuation strategies are critical for safeguarding human lives. This paper introduces a multi-objective optimization model that seeks to minimize both the overall transportation distance for affected individuals and the average unutilized space in designated evacuation centers. The model explicitly incorporates fairness, ensuring that all residents are equally prioritized during the evacuation process. We tested the model's applicability using a real-world scenario in Seaside, Oregon, which is a vulnerable town to frequent natural hazards. The case study aims to address the specific logistical challenges associated with evacuating a population of approximately 6,000 residents under tsunami hazard. Our analysis indicates that the transportation mode and capacity are pivotal variables for achieving an effective and equitable evacuation procedure. This research extends the existing literature on disaster preparedness by emphasizing the crucial role of transportation logistics in ensuring successful and fair evacuations.