绝热量子计算对最后一英里场景下运输优化的影响

Juan Francisco Ariño Sales, Raúl Andrés Palacios Araos
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摘要

在不断发展的全球贸易和供应链管理中,物流优化是一项严峻的挑战。本研究针对旅行推销员问题(TSP)的变体--车辆路由问题(VRP),提出了一种将经典计算方法与量子计算方法完美结合的新型混合解决方案。通过对我们的方法(包括算法选择、数据收集和计算过程)进行全面分析,我们深入了解了我们的混合解决方案与传统方法相比的效率和有效性。对 14 个数据集进行分析后得出的结果凸显了这种方法的优势和局限性,证明了它在解决 NP 难问题方面的潜力,并为物流优化算法领域做出了重大贡献。这项研究为物流优化技术的进步及其对提高供应链效率的潜在影响做出了积极贡献。
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Adiabatic quantum computing impact on transport optimization in the last-mile scenario
In the ever-evolving landscape of global trade and supply chain management, logistics optimization stands as a critical challenge. This study takes on the Vehicle Routing Problem (VRP), a variant of the Traveling Salesman Problem (TSP), by proposing a novel hybrid solution that seamlessly combines classical and quantum computing methodologies. Through a comprehensive analysis of our approach, including algorithm selection, data collection, and computational processes, we provide in-depth insights into the efficiency, and effectiveness of our hybrid solution compared to traditional methods. The results after analysis of 14 datasets highlight the advantages and limitations of this approach, demonstrating its potential to address NP-hard problems and contribute significantly to the field of optimization algorithms in logistics. This research offers promising contributions to the advancement of logistics optimization techniques and their potential implications for enhancing supply chain efficiency.
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