3756. Computational Performance of QAOA to Optimize Mesh Networks for Disaster Preparedness
Invited abstract in session TE-66: Applied Quantum Optimization, stream Quantum Optimization.
Tuesday, 14:15-15:45Room: JUR – Seminar-Raum 31
Authors (first author is the speaker)
| 1. | Emily Tucker
|
| Industrial Engineering, Clemson University | |
| 2. | Jack Layton
|
| Clemson University |
Abstract
We consider the motivating problem of prepositioning a mesh network of radio nodes in mountainous terrain prior to a disaster. A practical challenge is the obstructive effects of topology on the signal. We develop a mesh network design optimization model and implement the Quantum Approximate Optimization Algorithm (QAOA) as a heuristic. We evaluate QAOA’s computational performance under different objective functions and warm-starting strategies across realistic terrain and equipment parameter settings. Analyses are conducted on quantum hardware as well as compared with classical simulations.
Keywords
- Quantum Computing
- Disaster and Crisis Management
- Network Design
Status: accepted
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