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Quantum algorithms for optimised planning/scheduling applications

Quantum algorithms for optimised planning/scheduling applications
用于优化规划/调度应用的量子算法
批准号:
EP/R020426/1
负责人:
Ashley Montanaro
金额:
$6.31万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

项目摘要

项目成果

Ashley Montanaro的其他基金

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中文摘要
翻译
该项目将与主要的行业和学术合作伙伴密切合作,研究利用量子算法优化规划任务的技术和商业可行性。它旨在证明用量子算法增强现有人工智能(AI)规划技术的技术可行性,无论是作为完全量子还是混合解决方案,结合量子和传统计算方法。我们将进行实验,以建立使用早期量子退火算法增强人工智能规划技术的基准,然后确定如何使用其他通用量子计算或“电路模型”方法进一步增强它们。此外,该项目还将对量子增强优化规划解决方案进行市场评估,并确定将其商业化用于多个市场的商业可行性,包括电信网络优化,分销物流和运营规划。这将有助于激发潜在最终用户和量子计算供应商的更广泛兴趣,为特定市场开发优化工具,并为运输、物流、能源和金融带来潜在的重大生产力提升。
英文摘要
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.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Quantum speedup of branch-and-bound algorithms
分支定界算法的量子加速
DOI: 10.1103/physrevresearch.2.013056
发表时间: 2020
期刊: Physical Review Research
影响因子: 4.2
作者: [Montanaro A]
通讯作者: Montanaro A
DOI: 10.22331/q-2019-07-18-167
发表时间: 2019-07-18
期刊: QUANTUM
影响因子: 6.4
作者: [Campbell, Earl, Khurana, Ankur, Montanaro, Ashley]
通讯作者: Montanaro, Ashley
QuantAlgo: Quantum algorithms and applications
  • 批准号:
    EP/R043957/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $59.7万
  • 财政年份:
    2018
  • 负责人:
    Ashley Montanaro
  • 依托单位:
New insights in quantum algorithms and complexity
  • 批准号:
    EP/L021005/1
  • 项目类别:
    Fellowship
  • 资助金额:
    $107.19万
  • 财政年份:
    2014
  • 负责人:
    Ashley Montanaro
  • 依托单位:
New directions in quantum algorithms
  • 批准号:
    EP/G049416/2
  • 项目类别:
    Fellowship
  • 资助金额:
    $0.0万
  • 财政年份:
    2010
  • 负责人:
    Ashley Montanaro
  • 依托单位:
New directions in quantum algorithms
  • 批准号:
    EP/G049416/1
  • 项目类别:
    Fellowship
  • 资助金额:
    $26.63万
  • 财政年份:
    2009
  • 负责人:
    Ashley Montanaro
  • 依托单位:
国内基金
海外基金
固定参数可解算法在平面图问题的应用以及和整数线性规划的关系
  • 批准号:
    60973026
  • 项目类别:
    面上项目
  • 资助金额:
    32.0万元
  • 批准年份:
    2009
  • 负责人:
    鲁道夫
  • 依托单位:
Computational Methods for Analyzing Toponome Data