Improving Feasibility in Quantum Approximate Optimization Algorithm for Vehicle Routing via Constraint-Aware Initialization and Hybrid XY-X Mixing
The research addresses a major challenge in using Quantum Approximate Optimization Algorithm (QAOA) for Vehicle Routing Problems (VRP), which is finding solutions that are actually feasible. The authors combined a constraint-aware initialization strategy with a hybrid XY-X mixer. This combination consistently led to lower average energy and higher ratios of feasible solutions compared to standard QAOA, effectively guiding the quantum search toward valid routes.