2024/03/22 by Eneko Osaba, Osaba, Eneko, Esther Villar-Rodríguez +3 · 2 citations
Engineering · #Advanced Manufacturing and Logistics Optimization #Artificial Intelligence (cs.AI) #Emerging Technologies (cs.ET) #FOS: Computer and information sciences #Optimization and Packing Problems
paper · pdf · doi:10.48550/arxiv.2403.15114
openalex publication_date 2024/03/22 · openalex created_date 2024/03/26 · openalex updated_date 2026/07/28
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.