I-Corps: Leveraging the computational power of a quantum annealer to optimize the methods and technologies in the logistics and supply-chain industry

这个i-Corps项目的更广泛的影响/商业潜力是开发技术，以提高效率并降低决策过程中产生的成本，决策涉及多个变量以及这些变量的几种可能组合。这项技术利用量子计算机(QC)的强大功能，实现更快、更高效的计算潜力，帮助企业快速做出决策。这项拟议的技术可能会应用于金融、物流和供应链以及药物研发等几个行业领域。特别是，物流和供应链公司可以通过在路线优化、仓库管理、库存管理和最后一英里送货方面做出更快、更高效的决策，从这项技术中受益匪浅。这可能会让公司减少燃料排放，减少能源支出，并改善客户服务。公司还可以节省资源管理和减少判断错误，在这些情况下，节省的一小部分成本会带来大量的节省。从环境的角度来看，将这项技术商业化可能会有经济效益和积极的影响。这个i-Corps项目基于一套解决复杂分配问题的算法的开发。该解决方案基于新冠肺炎疫苗分销模式，旨在通过建议市县内企业实施的措施，为安全的重启过程提供建议和监测。这些算法还将提出有效的供应分配模式，以优化对有限资源的影响，并为潜在的大规模灾害制定和加强缓解程序和供应交付程序。这项拟议技术有可能帮助解决与紧急情况和减灾有关的关键因素，以及更好和更有效地分发货物。其目标是开发一种成熟的软件产品，供各种企业使用。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this I-Corps project is the development of technology to increase efficiency and reduce the costs incurred in decision-making that involves multiple variables along with several possible combinations of such variables. This technology leverages the power of a Quantum Computer (QC) for a faster and more efficient computational potential, which helps businesses in rapid decision making. This proposed technology may be applied to several industry segments such as finance, logistics and supply chain, and drug discovery. In particular, logistics and supply chain companies may benefit significantly from this technology by making faster and more efficient decisions on route to optimization, warehouse management, inventory management, and last-mile delivery. This may allow companies to reduce fuel emissions, spend less on energy, and improve customer service. Companies also may save on resource management and reduced errors in judgment, where a small fraction of cost savings result in large savings. Commercializing this technology may have an economic benefit as well as a positive impact from an environmental perspective.This I-Corps project is based on the development of a set of algorithms to solve complex distribution problems. Based on a COVID-19 vaccine distribution model, the solution targets advising and monitoring a safe reopening process by suggesting measures to be implemented by businesses within cities and counties. The algorithms will also suggest effective supply distributions patterns to optimize impact on limited resource and to develop and enhance mitigation procedures and supply delivery processes for potential large-scale disasters. This proposed technology has the potential to help address critical elements relevant to emergency and disaster mitigation as well as better and more efficient distributions of goods. The goal is to develop a full-fledged software product to be used by a variety of businesses.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.