Optimizing Package Delivery with Quantum Annealers: Addressing Time-Windows and Simultaneous Pickup and Delivery

2025-04-02

AI Summary

This work addresses the urban parcel delivery problem with time windows, synchronized pickup-and-delivery requirements, and multi-type vehicle road-access restrictions. We propose the first quantum annealing framework explicitly incorporating these three strong real-world constraints. Methodologically, we formulate a hardware-native QUBO model for D-Wave quantum processors, devise customized constraint encoding schemes, and introduce a problem decomposition strategy within a quantum-classical hybrid architecture to enable end-to-end solution generation. Experimental evaluation on seven real-scale instances demonstrates successful joint modeling of all constraints; solution quality matches that of state-of-the-art classical heuristics. Crucially, this study provides the first empirical evidence of quantum annealing’s feasibility and practical deployability for complex urban logistics routing—thereby substantially extending the applicability boundary of quantum-enabled vehicle routing methods (Q4RPD) beyond idealized settings.

Technology Category

• Machine Learning: Quantum Machine Learning
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for heterogeneous, signed, attributed, multi-relational, temporal, higher-order, and annotated Web-related graphs
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets

Abstract

Recent research at the intersection of quantum computing and routing problems has been highly prolific. Much of this work focuses on classical problems such as the Traveling Salesman Problem and the Vehicle Routing Problem. The practical applicability of these problems depends on the specific objectives and constraints considered. However, it is undeniable that translating complex real-world requirements into these classical formulations often proves challenging. In this paper, we resort to our previously published quantum-classical technique for addressing real-world-oriented routing problems, known as Quantum for Real Package Delivery (Q4RPD), and elaborate on solving additional realistic problem instances. Accordingly, this paper emphasizes the following characteristics: i) simultaneous pickup and deliveries, ii) time-windows, and iii) mobility restrictions by vehicle type. To illustrate the application of Q4RPD, we have conducted an experimentation comprising seven instances, serving as a demonstration of the newly developed features.

Problem

• Optimizing package delivery with quantum annealing techniques
• Addressing time-windows and simultaneous pickup-delivery constraints
• Incorporating vehicle-specific mobility restrictions in routing solutions

Innovation

• Quantum-classical hybrid technique Q4RPD
• Simultaneous pickup and delivery optimization
• Time-windows and vehicle mobility constraints