1452. Anticipatory Action for Floods: A Data-Driven Optimization Framework
Invited abstract in session MD-16: Food and Nutrition Security - Vulnerability, stream Sustainable Food & Agroforestry.
Monday, 14:30-16:00Room: Esther Simpson 2.07
Authors (first author is the speaker)
| 1. | Rein Lommerse
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| 2. | Thomas Breugem
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| Humanitarian Research Group, INSEAD | |
| 3. | Burcu Balcik
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| Ozyegin University |
Abstract
Flood occurrences are increasing globally, threatening food security by damaging crops, livestock, and storage facilities. Since 2000, flood-related disasters have risen by 134%, driven by climate change-induced extreme weather. While humanitarian disasters have surged in recent decades, advancements in flood forecasting enable proactive interventions. Such interventions are commonly termed anticipatory actions, an increasingly popular and cost-effective approach to humanitarian aid. We propose a novel framework for optimizing anticipatory actions, leveraging multi-stage stochastic optimization and optimal stopping theory to determine when and how to act. Applying our framework to flood data from the Brahmaputra River in Bangladesh, we demonstrate its effectiveness in enabling timely and efficient interventions, thereby strengthening food security and protecting vulnerable populations from hunger.
Keywords
- Stochastic Optimization
- Optimal Control
- OR in Environment and Climate change
Status: accepted
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