Quantum optimised train schedules

公共轨道交通网络的规划和运营涉及乘客服务、基础设施管理、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。数学优化是战略、战术和运营决策的组成部分；这包括列车路线和班次的线路规划、在现有基础设施下可行和稳健的规划时刻表、乘务管理，以及因应延误而重新安排列车时刻表。通常，这些优化问题对于实际网络规模的精确求解器来说是难以解决的；近似优化器用于提供更快的解，但解质量较低。使用量子计算机，Q-CTRL旨在提高快速获得的解决方案的质量；质量提高几个百分点就相当于运输时间的大幅改善，对延误的稳健性，以及运营成本和排放的减少。Q-CTRL正在与交通部(DFT)和Network Rail合作，解决大规模铁路网络和详细车站路线的列车时刻表优化问题。Q-CTRL将设计和部署一种量子算法，以在牛津量子电路(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可最大化硬件性能，与OQC最先进的量子计算机相结合，将提供原型列车调度解决方案，并提供加速路线图，以提供来自量子计算机的增强型解决方案。

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.Mathematical optimisation is integral to 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 but with lower solution quality. Using quantum computers, Q-CTRL aims 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 is working with the Department for Transport (DfT) and Network Rail to address train schedule optimisation both for large-scale rail networks, and for detailed station routing. Q-CTRL will design and deploy a quantum algorithm to perform train schedule optimisation on Oxford Quantum Circuits (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 prototype train scheduling solutions, and provide an accelerated roadmap to deliver enhanced solutions from quantum computers.