不确定条件下空中交通管理的跨境容量规划

IF 4.4 2区 工程技术 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Jan-Rasmus Künnen, Arne K. Strauss, Nikola Ivanov, Radosav Jovanović, Frank Fichert, Stefano Starita
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引用次数: 1

摘要

在欧洲空中交通管理(ATM)中,为每个空域提供多少容量是一个重要的决定,它必须在运营日之前几周甚至几个月做出决定。考虑到在此之前可能出现的需求不确定性以及容量供应的可变性(例如,由于天气),如果不能在需要的时间和地点提供容量,空域用户可能会面临高成本的位移(即延误和改道)。我们提出了一种新的容量共享方案,其中总容量的一部分可以灵活地部署在同一联盟的任何空域(单位成本增加)。这使我们能够对冲产能不足的风险。鉴于这一方案,我们寻求确定本地和跨境共享能力的最佳预算,从而实现最低的预期网络成本(即容量和流离失所成本)。为了确定最佳容量水平,我们需要解决一个分两阶段的报摊问题:首先确定每个空域的容量,在不确定的需求和容量供应中断出现后,我们需要确定航班路线(包括延误)以及每个空域的扇区开放方案,以最大限度地降低成本。我们提出了一种模拟优化方法来搜索最具成本效益的容量水平(在第一阶段),并提出了一种启发式方法来解决路由和扇区开放问题(在第二阶段),即[公式:见文本]-hard。我们在一项大型模拟研究中测试了我们的方法,该研究基于西欧空域约3000个航班的真实数据。我们发现我们的随机方法在使用更少的计算资源的同时显著降低了相对于确定性基准的网络成本。对不同容量共享设置的实验表明,如果跨境共享容量,总可变成本可以降低8%以上:尽管我们要求容量共享下的空域不能比不共享时运行更低的容量(这是为了避免用工资水平较低的国家的昂贵的空中交通管制员来替代)。我们还发现,使用不同的技术提供商是从能力共享中获益的主要障碍,而在同一国家的不同空域共享能力可能更可取。历史:本文已被《运输科学与物流新课题》运输科学特刊接受。资助:本研究由地平线2020框架计划[893380]支持。补充材料:在线附录可在https://doi.org/10.1287/trsc.2023.1210上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cross-Border Capacity Planning in Air Traffic Management Under Uncertainty
In European air traffic management (ATM), it is an important decision how much capacity to provide for each airspace, and it has to be made weeks or even months in advance of the day of operation. Given the uncertainty in demand that may materialize until then along with variability in capacity provision (e.g., due to weather), Airspace Users could face high costs of displacements (i.e., delays and reroutings) if capacity is not provided where and when needed. We propose a new capacity sharing scheme in which some proportion of overall capacities can be flexibly deployed in any of the airspaces of the same alliance (at an increased unit cost). This allows us to hedge against the risk of capacity underprovision. Given this scheme, we seek to determine the optimum budget for capacities provided both locally and in cross-border sharing that results in the lowest expected network costs (i.e., capacity and displacement costs). To determine optimum capacity levels, we need to solve a two-stage newsvendor problem: We first decide on capacities to be provided for each airspace, and after uncertain demand and capacity provision disruptions have materialized, we need to decide on the routings of flights (including delays) as well as the sector opening scheme of each airspace to minimize costs. We propose a simulation optimization approach for searching the most cost-efficient capacity levels (in the first stage), and a heuristic to solve the routing and sector opening problem (in the second stage), which is [Formula: see text]-hard. We test our approach in a large-sized simulation study based on real data covering around 3,000 flights across Western European airspace. We find that our stochastic approach significantly reduces network costs against a deterministic benchmark while using less computational resources. Experiments on different setups for capacity sharing show that total variable costs can be reduced by more than 8% if capacity is shared across borders: even though we require that no airspace can operate lower capacities under capacity sharing than without (this is to avoid substitution of expensive air traffic controllers with those in countries with a lower wage level). We also find that the use of different technology providers is a major obstacle to reap the benefits from capacity sharing and that sharing capacities across airspaces of the same country may instead be preferred. History: This paper has been accepted for the Transportation Science Special Issue on Emerging Topics in Transportation Science and Logistics. Funding: This work was supported by the Horizon 2020 Framework Programme [893380]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2023.1210 .
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来源期刊
Transportation Science
Transportation Science 工程技术-运筹学与管理科学
CiteScore
8.30
自引率
10.90%
发文量
111
审稿时长
12 months
期刊介绍: Transportation Science, published quarterly by INFORMS, is the flagship journal of the Transportation Science and Logistics Society of INFORMS. As the foremost scientific journal in the cross-disciplinary operational research field of transportation analysis, Transportation Science publishes high-quality original contributions and surveys on phenomena associated with all modes of transportation, present and prospective, including mainly all levels of planning, design, economic, operational, and social aspects. Transportation Science focuses primarily on fundamental theories, coupled with observational and experimental studies of transportation and logistics phenomena and processes, mathematical models, advanced methodologies and novel applications in transportation and logistics systems analysis, planning and design. The journal covers a broad range of topics that include vehicular and human traffic flow theories, models and their application to traffic operations and management, strategic, tactical, and operational planning of transportation and logistics systems; performance analysis methods and system design and optimization; theories and analysis methods for network and spatial activity interaction, equilibrium and dynamics; economics of transportation system supply and evaluation; methodologies for analysis of transportation user behavior and the demand for transportation and logistics services. Transportation Science is international in scope, with editors from nations around the globe. The editorial board reflects the diverse interdisciplinary interests of the transportation science and logistics community, with members that hold primary affiliations in engineering (civil, industrial, and aeronautical), physics, economics, applied mathematics, and business.
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