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Mathematical models and algorithms for allocating scarce airport resources (OR-MASTER)

分配稀缺机场资源的数学模型和算法（OR-MASTER）

基本信息

批准号：
EP/M020258/1
负责人：
Konstantinos Zografos
金额：
$ 288.28万
依托单位：
Lancaster University
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
起止时间：
2015 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FM020258%2F1
关键词：
Mathematical models algorithms allocating scarce

项目摘要

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.

英国、欧洲和世界其他地区主要机场的拥堵是一个严重且日益严重的问题。希思罗机场已经面临着一天中大部分时间严重拥堵的问题，而盖特威克机场的需求预计到2025年将超过每天17个小时的容量。根据Eurocontrol的一项研究，到2030年，138个Eurocontrol统计参考区（ESRA）机场的计划容量预计将增加41%，在最有可能的预测增长情景中，需求超过机场容量多达230万个航班（或11%）。机场容量的开发和部署是一个重大的社会问题，在英国和世界各地引起了激烈的公众辩论。拥挤机场的容量以时隙表示。时隙标识了特定日期的一段时间间隔，在此期间，承运人被允许使用机场基础设施降落或起飞。目前的时隙分配程序（阿利亚其他外）不受以下限制：（1）对涉及多个利益攸关方的目标和业务/监管制约因素进行简单建模，2）对机场网络中遇到的相互作用的捕获不足。3）使用经验或特设过程来确定（而不是计算）申报容量，这既没有解决机场容量评估中涉及的不确定性，也没有解决实际问题的复杂性和规模，即使是在单个机场的水平上。因此，现有的分配机场容量的方法在许多关键方面不能反映真实的世界所呈现的复杂性。这造成了分配效率低下，这反过来又导致机场容量利用率低下，对机场收入、航空公司运营成本、为乘客提供的服务水平和环境产生重大负面影响。因此，迫切需要迎接重大科学挑战，开发新的数学模型和解决方案，以改变机场时隙分配过程及其相关结果。该计划的赠款旨在为一个机场和一个机场网络提供资金。将开发和分析数学模型，这些模型考虑到所有利益攸关方的目标和要求，并考虑到广泛的业务和监管限制。所提出的方案的内在复杂性和它的大规模（特别是对于网络范围的时隙分配的情况下）将意味着它将提供一个很好的测试平台，为开发新的算法和超算法的大规模复杂调度问题更广泛。该项目将开发和测试的算法将为其他类型的交通网络（包括铁路网络）中出现的复杂的大规模容量分配问题提供必要的支持。此外，它还可以扩展到具有类似问题结构的其他类型的网络，例如能源和电信领域的网络。开发的模型和解决方案技术将支持新型决策支持系统的开发，这些系统有可能对机场运营产生重大影响。该研究团队在数学建模、启发式开发、随机优化、机场时隙分配、机场管理和性能评估等领域具有国际领先地位。它在与各类利益攸关方的研究合作方面有着良好的记录。它将与一系列令人印象深刻的领先行业利益相关者密切合作，以确保这项工作在工业上和科学上都是最前沿的。