467. A Distributionally Robust Approach for Urban Search and Rescue Location-Routing Problem
Invited abstract in session TB-55: Robust and Stochastic Models in Disaster Management, stream Humanitarian Operations.
Tuesday, 10:30-12:00Room: Liberty 1.09
Authors (first author is the speaker)
| 1. | Kamran Sarmadi
|
| Queen Mary University of London | |
| 2. | Mehdi Amiri-Aref
|
| Kedge Business School |
Abstract
We address a multi-period location-routing problem under uncertain demand and travel times in disaster management. Our proposed optimisation model integrates strategic facility location with dynamic routing to guide search-and-rescue teams post-disaster. We use a distributionally robust optimisation framework with joint chance constraints to enhance tractability via Bonferroni’s inequality and constraint approximation. The methodology is tested on a case study in Santa Cruz County, California, a region prone to earthquakes. Numerical results highlight how our method aids decision-makers in optimising facility placement and team deployment to maximise rescue rates in uncertain environments
Keywords
- Humanitarian Applications
- Location
- Robust Optimization
Status: accepted
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