Research focused on the conjunction between quantum computing and routing problems has been very prolific in recent years. Most of the works revolve around classical problems such as the Traveling Salesman Problem or the Vehicle Routing Problem. The real-world applicability of these problems is dependent on the objectives and constraints considered. Anyway, it is undeniable that it is often difficult to translate complex requirements into these classical formulations.The main objective of this research is to present a solving scheme for dealing with realistic instances while maintaining all the characteristics and restrictions of the original real-world problem. Thus, a quantum-classical strategy has been developed, coined Q4RPD, that considers a set of real constraints such as a heterogeneous fleet of vehicles, priority deliveries, and capacities characterized by two values: weight and dimensions of the packages. Q4RPD resorts to the Leap Constrained Quadratic Model Hybrid Solver of D-Wave. To demonstrate the application of Q4RPD, an experimentation composed of six different instances has been conducted, aiming to serve as illustrative examples.

翻译：近年来，量子计算与路径规划问题交叉领域的研究成果极为丰硕。大多数工作围绕经典问题展开，如旅行商问题或车辆路径问题。这些问题的实际应用价值取决于所考虑的目标与约束条件。无论如何，不可否认的是，将复杂需求转化为这些经典问题形式往往存在困难。本研究的主要目标是提出一种求解方案，能够在处理现实场景实例的同时，完整保留原始实际问题的所有特征与限制条件。为此，我们开发了一种量子-经典混合策略——Q4RPD，该策略综合考虑了现实约束条件，包括异构车辆车队、优先级配送、以及由包裹重量和尺寸双指标定义的运载容量限制。Q4RPD借助D-Wave的Leap约束二次模型混合求解器实现。为展示Q4RPD的应用效能，我们设计了包含六个不同实例的实验组，旨在提供具有示范意义的应用案例。