Quantum Annealing Solutions for Drone Route Planning Problems
We present annealing solutions for route optimization problems for unmanned aerial vehicles (UAVs), The route planning problem is a generalised version of the Travelling Salesman Problem which has many applications in logistics planning. Our annealing solutions combine classical algorithms with quantum/digital annealers specifically designed for quadratic optimization problems and shows improvements over generic traditional solvers such as Gurobi. We empirically test the solvability of our annealing solutions on both hand-crafted hard test cases as well as simulated ‘real-world’ examples of urban environments where the operations of the UAVs can be affected by the direction and intensity of wind, which is conditioned by the presence of buildings.
Authors
- Daniele Di Lorenzo
- Francisco Chinesta
- Philippe Codognet (ORCID: https://orcid.org/0000-0002-6254-6389)
- Richard Hua
Institutions
- ESI Group (France) (FR)
- Centre National de la Recherche Scientifique (FR)
- Arts et Métiers (FR)
- Sorbonne Université (FR)
- Japanese-French Laboratory for Informatics (JP)
- The University of Tokyo (JP)
Publication Details
- Published
- 2024-09-15
- DOI
- https://doi.org/10.1109/qce60285.2024.00076
- Citations
- 2
- Primary Topic
- Quantum Computing Algorithms and Architecture
- Type
- article
- Field-Weighted Citation Impact
- 0.69