Quantum algorithms for optimised planning/scheduling applications

This project will investigate the technical and business feasibility of exploiting quantum algorithms for optimised planning tasks, in close collaboration with key industry and academic partners. It aims to prove the technical feasibility of enhancing existing artificial intelligence (AI) planning techniques with quantum algorithms, either as fully quantum or hybrid solutions, combining both quantum and conventional computing methods. We will perform experiments to establish benchmarks for enhancing AI planning techniques with early quantum annealing algorithms, and then determine how they might be further enhanced with other universal quantum computing or 'circuit-model' approaches. In addition, this project will perform a market assessment for quantum-enhanced optimised planning solutions and determine the business feasibility of commercialising them for several markets, including telecoms network optimisation, distribution logistics and operational planning. This will help to stimulate wider interest with potential end-users and quantum computing vendors to develop optimisation tools for specific markets, and deliver potential major productivity gains for transport, logistics, energy and finance.

Economic: In addition to economic benefits to our industry partner BT in telecom optimisation, the outputs of this feasibility study will stimulate wider interest in quantum-enhanced tools not only with innovation workshop participants, but also with other potential industry end users, who will receive our reports. It will also encourage other quantum computing vendors (including large technology companies and academic spin-offs) to develop optimisation tools for specific markets, and others in the supply chain to integrate early quantum annealers within hybrid solutions, as is already happening in the finance sector. Such optimisation products could generate large productivity gains for transport, logistics, energy, and retail. It could also disrupt key markets where UK already has strong positions, such as finance, aerospace and pharmaceuticals, and enable growth in new emerging markets that could also benefit from quantum-enhanced optimisation (e.g. blockchain).

Social: The social impact of wider introduction of optimisation tools could lead to better and earlier recognition of fraud/criminal activities, especially organised crime and deterence for specific classes of crime (e.g. cyber/financial fraud) which have been increasing greatly over the past few years, rising from $400Bn (2015) to $2trillion (2019). Optimisation tools could lead to better government social policy, financial regulation and impact of legislation on wider society. The World Development Bank Report (1997) determined the projected benefit on GDP of better regulation/de-regulation on developed countries ranged from 0.3% (US/Germany) to 18.7% (Japan), with the EU (3-7%).

Environmental: Better optimisation could lead to less traffic/pollution on transport networks, less resources used (materials/fuel) and less destructive failures due to predictive analytics. Not every vehicle would require a quantum processor, since optimisation solutions would most likley be accessed from cloud-based quantum information services.

Regional/national/global: Most of the potential impacts of quantum-enhanced optimisation tools described above have been highlighted at the regional/national/global level, including optimisation for telecoms/transport/logistics/energy grid networks, manufacturing/predictive fault management, regulatory compliance and complex plan recognition for cyber threats, financial fraud and other criminal behaviours.