Quantum Approximate Multi-Objective Optimization in Routing Problems
The study tested a Quantum Approximate Optimization Algorithm (QAOA) parameter transfer strategy for solving multi-objective routing problems like TSP and VRP. The method reuses parameters trained on smaller graphs to speed up solving complex, real-world instances. Results show this transfer effectively generates Pareto fronts with better coverage than classical methods while requiring less computation.