GOALI: Demand Driven Fleet Management Analysis, Models, and Algorithms for the Airline Industry

GOALI：航空业需求驱动的机队管理分析、模型和算法

• 批准号: 0245643
• 负责人: Hanif Sherali
• 金额: $ 34.78万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-15 至 2007-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0245643&HistoricalAwards=false
• 关键词: GOALI; Demand; Driven; Fleet; Management

This research project proposes to focus on an essential aspect of airline supply management, namely, the fleet assignment decision, and its effective coordination with demand under conditions of uncertainty. The intent is to develop and implement general models and algorithms in concert with our industrial partner: United Airlines, in order to ensure the transfer of technology to the airline industry. The current airline practice is to assign aircraft capacity to scheduled flights well in advance of departures. This is due to the dependency between the fleet assignment decision and other airline processes. At such an early stage, however, the high uncertainty of demand poses a major impediment for airlines to best match aircraft capacities with the final demand. On the other hand, the accuracy of demand forecasts improves markedly over time. Thus, it becomes advantageous to postpone irrevocable fleeting decisions to as great a future extent as possible, and to inject sufficient flexibility in the prescribed decisions so as to facilitate the ability to make future revisions within the operational constraints. To accomplish this, we propose a three-stage dynamic supply management framework that coordinates the initial fleet assignment model with a pair of downstream demand driven re-fleeting and swapping models in a manner designed to exploit the flexibility in the system, while incorporating progressively more accurate demand forecasts obtained as departures approach. The intent is to provide sufficient flexibility in the initial fleet assignment decisions to permit effective subsequent re-fleeting decisions so as to promote a better matching of demand with supply.If successful, the impact of our proposed research contributions will be: (1) to promote improvedsupply management decisions in the airline industry, while considering the interactions betweenthe initial fleeting, later re-fleeting, and swapping models within this framework; and (2) toprescribe effective solution approaches for the various models at each stage of this process, whichcan be extended to other similar manufacturing and service industrial environments. Inconducting this study, we propose to investigate several model enhancements to improverepresentability in practice by incorporating various features such as path-level and fare-classbased demands, recapture of spilled passengers, day-of-week demand variations, andmaintenance considerations. We hope thereby to help eliminate several critical weaknessesassociated with the traditional fleet assignment process, lend insights into improving operations,and achieve a demonstrable advance in the state-of-the-art in practice.

本研究计画将针对航空公司供应管理的一个重要方面，即机队分配决策，以及在不确定条件下与需求的有效协调。其目的是与我们的工业合作伙伴联合航空公司合作开发和实施通用模型和算法，以确保技术转移到航空业。 目前航空公司的做法是在起飞前提前为定期航班分配飞机运力。这是由于机队分配决策与其他航空公司流程之间的依赖性。然而，在这样的早期阶段，需求的高度不确定性对航空公司最好地将飞机容量与最终需求相匹配构成了重大障碍。另一方面，需求预测的准确性随着时间的推移而显著提高。因此，将不可撤销的短暂决定推迟到尽可能大的未来范围，并在规定的决定中注入足够的灵活性，以促进在操作限制内进行未来修改的能力，这是有利的。 为了实现这一目标，我们提出了一个三阶段的动态供应管理框架，协调初始的车队分配模型与一对下游需求驱动的重新飞行和交换模型的方式，旨在利用系统的灵活性，同时将逐步更准确的需求预测作为出发的方法。 其目的是在最初的机队分配决策中提供足够的灵活性，以便有效地进行后续的重新飞行决策，从而促进需求与供应的更好匹配。如果成功，我们建议的研究贡献将产生以下影响：（1）促进航空业改进供应管理决策，同时考虑最初的短暂飞行，后来的重新飞行，（2）为该过程的各个阶段的各种模型制定有效的求解方法，并可推广到其他类似的制造业和服务业环境中。在进行这项研究，我们建议调查几个模型增强，以提高representability在实践中结合各种功能，如路径水平和基于票价等级的需求，夺回溢出的乘客，一周中的需求变化，和维护的考虑。我们希望借此帮助消除与传统机队分配过程相关的几个关键弱点，为改进运营提供见解，并在实践中实现最先进的可证明的进步。