University of Calabria scientists solve thirty-node Travelling Salesman Problem with hybrid quantum-classical method
Updated
Updated · Quantum Zeitgeist · Apr 27
University of Calabria scientists solve thirty-node Travelling Salesman Problem with hybrid quantum-classical method
3 articles · Updated · Quantum Zeitgeist · Apr 27
Led by Alessia Ciacco, the team used dynamic subtour elimination and arc filtering to achieve solutions previously limited to eight nodes, leveraging the D-Wave quantum platform.
Their integrated framework reduced model size and improved computational performance across classical, direct quantum, and hybrid strategies, marking a significant advance in combinatorial optimisation.
This breakthrough enables tackling larger, real-world logistical problems and lays groundwork for future research into more efficient quantum algorithms and noise mitigation techniques for complex optimisation challenges.
How does D-Wave's annealing method for optimization stack up against rivals' gate-model quantum computers?
When will this quantum method scale from 30 nodes to solve real-world industrial optimization problems?
What is the next major barrier to scaling this quantum approach to problems with thousands of variables?
Beyond logistics, what other scientific discoveries are being unlocked by today’s noisy quantum computers?
Can the best classical supercomputers still outperform this new hybrid quantum approach on complex routing problems?
Is the key to quantum power better qubits, or smarter AI-driven software that corrects their errors?