AI RESEARCH
Hybrid Quantum Reinforcement Learning with QAOA for Improved Vehicle Routing Optimization
arXiv CS.LG
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ArXi:2605.01574v1 Announce Type: new Vehicle Routing Problem (VRP) is one of the most complex NP-hard combinatorial optimization problem in transportation and logistics that requires a dynamic solution approach. In this paper we present a new hybrid approach that combines the Quantum Approximate Optimization Algorithm (QAOA) into the QRL policy network, instead of the usual variational layers, QAOA mixing and cost Hamiltonian layers.