4771. An iterative approach for solving the Traveling Salesman Problem with classical and quantum optimization
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. | Alessia Ciacco
|
| Department of Mechanical, Energy, and Management Engineering, University of Calabria | |
| 2. | Luigi Di Puglia Pugliese
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| Istituto di Calcolo e Reti ad Alte Prestazioni, Consiglio Nazionale delle Ricerche | |
| 3. | Francesca Guerriero
|
| D.I.M.E.G.: Mechanical, Energy and Management Engineering, University of Calabria |
Abstract
The Traveling Salesman Problem is a classical NP-hard combinatorial optimization problem, where a key challenge is the large number of subtour elimination constraints required for feasibility. We adopt an iterative approach, based on well-established Operations Research techniques, where subtour constraints are generated dynamically and combined with preprocessing to reduce arcs. We evaluate classical and quantum methods. Results show reduced model size and improved performance, demonstrating quantum approaches benefit significantly from these techniques over formulations without them.
Keywords
- Quantum Computing
- Transportation
- Logistics
Status: accepted
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