Fairness-Driven Multi-Objective Optimization for Evacuation Planning in Natural Disasters
Document Type
Conference Proceeding
Publication Date
1-1-2024
Abstract
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.
Publication Source (Journal or Book title)
International Conference on Transportation and Development 2024: Transportation Planning, Operations, and Transit - Selected Papers from the International Conference on Transportation and Development 2024
First Page
170
Last Page
180
Recommended Citation
Gupta, H., Gonzalez, A., Jnad, R., & Kameshwar, S. (2024). Fairness-Driven Multi-Objective Optimization for Evacuation Planning in Natural Disasters. International Conference on Transportation and Development 2024: Transportation Planning, Operations, and Transit - Selected Papers from the International Conference on Transportation and Development 2024, 170-180. https://doi.org/10.1061/9780784485521.016