1933. Improving Essential Services Accessibility Under Natural Disaster Risks using Multi-Objective Optimization: A Case Study for Cao Bang
Invited abstract in session TB-23: OR for Socio-Humanitarian Development , stream OR for Societal Development.
Tuesday, 10:30-12:00Room: Esther Simpson 3.01
Authors (first author is the speaker)
| 1. | Britt van Veggel
|
| Business Analytics, University of Amsterdam | |
| 2. | Maria Paola Scaparra
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| Kent Business School, University of Kent | |
| 3. | Ngoc Dao
|
| University of Kent, Kent Business School |
Abstract
Vietnam faces significant risks from natural disasters, with 46% of its population exposed to severe flooding. Landslides and floods frequently damage infrastructure, disrupting access to healthcare, education, and food. These challenges are particularly severe in northern mountainous regions like Cao Bang. This research focuses on optimizing disaster-resilient infrastructure investments to ensure equitable access to essential services under varying disaster conditions. We develop a multi-objective optimization model to improve accessibility by determining optimal infrastructure investments under different disaster scenarios. The model balances two objectives: maximizing service coverage and ensuring fairness by prioritizing high-resilience improvements for infrastructure used by lower-income populations. We also explore a multi-period planning framework to strategically schedule investments within budget constraints. To solve this large-scale problem, we implement a Non-Dominated Sorting Genetic Algorithm II. Our approach integrates data existing data and by combining information from government sources. We collaborate with local institutions for hazard maps and cost estimates. Preliminary findings highlight accessibility gaps and and identify critical infrastructure vulnerabilities.
Keywords
- OR in Development
- OR in Environment and Climate change
- Disaster and Crisis Management
Status: accepted
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