Quantum algorithms for optimised planning/scheduling applications
Quantum algorithms for optimised planning/scheduling applications
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 --
中文摘要
该项目将与关键的行业和学术合作伙伴密切合作,调查利用量子算法优化计划任务的技术和商业可行性。它的目的是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解决方案还是混合解决方案,结合量子和传统计算方法。我们将进行实验,以建立基准,以增强早期量子退火算法的人工智能规划技术,然后确定如何使用其他通用量子计算或“电路模型”方法进一步增强这些技术。此外,该项目将对量子增强型优化计划解决方案进行市场评估,并确定它们在几个市场商业化的商业可行性,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率提升。
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
-
批准号:60601030
-
项目类别:青年科学基金项目
-
资助金额:17.0万元
-
批准年份:2006
-
负责人:Axel Mosig
-
依托单位: