Quantum optimised Electric Vehicle charger locations

量子优化的电动汽车充电器位置

• 批准号: 10085982
• 金额: $ 8.35万
• 依托单位: Q-CTRL UK LIMITED
• 依托单位国家: 英国
• 项目类别: Small Business Research Initiative
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10085982
• 关键词: Quantum; optimised; Electric; Vehicle; charger

Quantum optimised train schedules Planning and operation of public rail transport networks involves a complex balance of passenger service, infrastructure management for feasible and safe operations, and network resilience to disruption. To effectively meet these objectives, fast and high-quality optimisations are needed. Optimisation supports strategic, tactical, and operational decisions; this includes line planning of train routes and frequencies, planning schedules that are feasible and robust with available infrastructure, crew management, and train timetable rescheduling in response to delays. Typically these optimisation problems are intractable for exact solvers on the scale of practical networks; approximate optimisers are used to provide faster solutions at the cost of lower solution quality. Using quantum computers, Q-CTRL expects to improve the quality of solutions obtained rapidly; a few percent improvement in quality can correspond to substantial improvements in transit time, robustness to delays, and reductions in operating costs and emissions.Q-CTRL will work with the Department for Transport (DfT) and Network Rail to address key use cases such as train schedule optimisation subject to infrastructure capacity, and disruption response management. Q-CTRL will design and deploy a quantum algorithm to perform train schedule optimisation on OQC quantum computers. The combination of Q-CTRL's world-leading expertise in quantum solution design and infrastructure software to maximise hardware performance, together with OQC's state-of-the-art quantum computers, will provide a clear picture of current quantum computing performance for this high-priority application, and an accelerated roadmap to deliver enhanced solutions from quantum computers.

公共轨道交通网络的规划和运营涉及客运服务、可行和安全运营的基础设施管理以及网络对中断的恢复能力之间的复杂平衡。为了有效地实现这些目标，需要快速和高质量的优化。优化支持战略、战术和操作决策；这包括列车路线和频率的线路规划，可行的和健全的基础设施规划时间表，机组管理，以及响应延误的列车时间表重新安排。通常，这些优化问题对于实际网络规模的精确求解者来说是难以解决的；近似优化器用于以较低的解决方案质量为代价提供更快的解决方案。使用量子计算机，Q-CTRL期望快速提高解的质量；质量的几个百分点的改进可以对应于运输时间的实质性改进，对延迟的稳健性，以及运营成本和排放的减少。Q-CTRL将与运输部（DfT）和网络铁路合作，解决关键用例，如根据基础设施容量优化列车时刻表，以及中断响应管理。Q-CTRL将设计和部署一种量子算法，在OQC量子计算机上执行列车时刻表优化。Q-CTRL在量子解决方案设计和基础设施软件方面的世界领先专业知识的结合，将最大限度地提高硬件性能，再加上OQC最先进的量子计算机，将为这一高优先级应用提供当前量子计算性能的清晰画面，并加速路线图，从量子计算机提供增强的解决方案。