Mathematical models and algorithms for allocating scarce airport resources (OR-MASTER)
Mathematical models and algorithms for allocating scarce airport resources (OR-MASTER)
批准号:
EP/M020258/1
负责人:
Konstantinos Zografos
金额:
$288.28万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2015
资助国家:
英国
项目状态:
未结题
起止时间:
2015 至 --
中文摘要
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英文摘要
Congestion at major airports in the UK and across Europe and the rest of the world is a serious and growing problem. Already Heathrow faces problems occasioned by serious congestion for a major part of the day while at Gatwick demand is expected to exceed capacity for 17 hours per day by 2025. According to a Eurocontrol study, planned capacity at the 138 Eurocontrol Statistical Reference Area (ESRA) airports is expected to increase by 41% in total by 2030, with demand exceeding airport capacity by as much as 2.3 million flights (or 11%) in the most-likely forecast growth scenario. The development and deployment of airport capacity is a major societal issue engendering intense public debate in the UK and around the world.Capacity at congested airports is expressed in slots. A slot identifies a time interval on a specific date during which a carrier is permitted to use the airport infrastructure for landing or take-off. Current slot allocation procedures suffer (inter alia) from the following limitations:1)Simplistic modelling of the objectives and operational/regulatory constraints bearing on the multiple stakeholders involved in (and affected by) the slot allocation process.2)Insufficient capture of the interactions encountered in airport networks.3)The use of empirical or ad hoc processes for determining (rather than computing) declared capacity which address neither the uncertainties involved in airport capacity assessment nor the complexity and size of the real-world problem, even at the single-airport level.Consequently, existing approaches to the allocation of airport capacity fail in a number of critical ways to reflect the complexities presented by the real world. This creates allocation inefficiencies which, in turn, result in poor airport capacity utilisation with significant negative impacts on airport revenues, airline operating costs, the level of service offered to passengers and the environment.There is thus a pressing need to meet the major scientific challenge of developing novel mathematical models and solution approaches to transform the airport slot allocation process and its associated outcomes. The programme grant aims to do just that for a single airport and for a network of airports. Mathematical models will be developed and analysed which consider the objectives and requirements of all stakeholders and which take account of a wide range of operational and regulatory constraints. The intrinsic complexity of the proposed programme and its large scale (especially for the case of the network-wide slot allocation) will mean that it will provide an excellent test-bed for the development of new heuristics and hyper heuristics for large scale complex scheduling problems more widely. Algorithms that will be developed and tested by this project will provide essential support for the complex large scale capacity allocation problems that arise in other types of transportation networks, including rail networks. In addition, it could extend to other types of networks that share similar problem structures, such as those in energy and telecommunications.The models and solution techniques developed will underpin the development of novel decision support systems which have the potential to make a major impact on airport operations. The research team has an internationally leading profile in the areas of mathematical modelling, heuristic development, stochastic optimization, airport slot allocation, airport management and performance assessment. It has an excellent track record of research cooperation with all categories of stakeholders. It will cooperate closely with an impressive array of leading industry stakeholders in order to make sure that the work is as cutting edge industrially as it is scientifically.
期刊论文(10)
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Modelling and Solving the Single-Airport Slot Allocation Problem
建模并解决单机场航班时刻分配问题
DOI:
--
发表时间:
2022
期刊:
影响因子:
--
作者:
[Fotios A. Katsigiannis]
通讯作者:
Fotios A. Katsigiannis
Calculating block time and consumed fuel for an aircraft model
计算飞机模型的阻塞时间和消耗的燃料
DOI:
10.1017/aer.2020.137
发表时间:
2021
期刊:
The Aeronautical Journal
影响因子:
--
作者:
[De Lemos F]
通讯作者:
De Lemos F
Introducing flexibility and demand-based fairness in slot scheduling decisions
在时段调度决策中引入灵活性和基于需求的公平性
DOI:
--
发表时间:
2018
期刊:
影响因子:
--
作者:
[Fairbrother J]
通讯作者:
Fairbrother J
DOI:
10.1016/j.ejor.2020.10.003
发表时间:
2020-10
期刊:
Eur. J. Oper. Res.
影响因子:
--
作者:
[Jamie Fairbrother;K. Zografos]
通讯作者:
Jamie Fairbrother;K. Zografos
DOI:
10.1287/trsc.2019.0926
发表时间:
2019-12
期刊:
Transp. Sci.
影响因子:
--
作者:
[Jamie Fairbrother;K. Zografos;K. Glazebrook]
通讯作者:
Jamie Fairbrother;K. Zografos;K. Glazebrook
共 9 条
RESilient Emergency Preparedness for Natural Disaster Response through Operational Research(RESPOND-OR)
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批准号:EP/T003979/1
-
项目类别:Research Grant
-
资助金额:$65.74万
-
财政年份:2019
-
负责人:Konstantinos Zografos
-
依托单位:
国内基金
海外基金
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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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批准号:--
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项目类别:合作创新研究团队
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资助金额:--
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批准年份:2024
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负责人:姚韬
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依托单位:
河北南部地区灰霾的来源和形成机制研究
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批准号:41105105
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资助金额:25.0万元
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批准年份:2011
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负责人:王丽涛
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依托单位:
保险风险模型、投资组合及相关课题研究
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批准号:10971157
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项目类别:面上项目
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资助金额:24.0万元
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批准年份:2009
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负责人:胡亦钧
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依托单位:
RKTG对ERK信号通路的调控和肿瘤生成的影响
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批准号:30830037
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项目类别:重点项目
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批准年份:2008
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负责人:陈雁
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依托单位:
新型手性NAD(P)H Models合成及生化模拟
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批准号:20472090
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项目类别:面上项目
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资助金额:23.0万元
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批准年份:2004
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负责人:王乃兴
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依托单位: