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3364. Post-disaster Relief Distribution Optimization Framework in Salgar, Colombia
Invited abstract in session WA-21: Post-Disaster Relief Distribution, stream OR in Humanitarian Operations (HOpe).
Wednesday, 8:30-10:00Room: 49 (building: 116)
Authors (first author is the speaker)
| 1. | Juana Jaramillo-Rios
|
| Department of Civil Engineering, Universidad Nacional de Colombia | |
| 2. | Paula Penagos
|
| University of Missouri-St. Louis | |
| 3. | Carlos A. Gonzalez-Calderon
|
| Universidad Nacional de Colombia at Medellin |
Abstract
Humanitarian logistics is crucial in crisis and disaster scenarios, enhancing system resilience and facilitating rapid restoration. Post-disaster relief distribution is a critical challenge, requiring efficient and effective relief to minimize suffering. The complexity of relief distribution involves navigating damaged infrastructure, coordinating with stakeholders, and adapting to dynamic conditions. The social impact of relief distribution, especially on vulnerable populations, is paramount. Ensuring accessibility to essential resources and efficient connectivity can mitigate suffering. Colombia, a developing country, is most vulnerable to natural disasters, climate-related risks, and economic instability. The 2015 flash flood in Salgar, Antioquia, caused 93 deaths and affected over 1,263 people. The community faces challenges in post-disaster relief distribution, including damage assessment, accessibility, resource allocation, and efficient node placement. This research proposes an optimization framework for transportation networks to improve relief distribution efficiency and effectiveness in disaster-affected areas, leveraging a mathematical model. The framework uses multidisciplinary methods, including qualitative data analysis from humanitarian logistics experts and optimization algorithms for quick decision-making. It optimizes aid distribution to maximize coverage, minimize response times, and allocate resources.
Keywords
- Humanitarian Applications
- Transportation
- Optimization Modeling
Status: accepted
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