Airline Timetable Development and Fleet Assignment Incorporating Passenger Choice

运筹学 计算机科学 启发式 利润(经济学) 背景(考古学) 机组调度 车队管理 调度(生产过程) 数学优化 工程类 经济 电信 生物 操作系统 数学 古生物学 微观经济学
作者
Keji Wei,Vikrant Vaze,Alexandre Jacquillat
出处
期刊:Transportation Science [Institute for Operations Research and the Management Sciences]
卷期号:54 (1): 139-163 被引量:49
标识
DOI:10.1287/trsc.2019.0924
摘要

Flight timetabling can greatly impact an airline’s operating profit, yet data-driven or model-based solutions to support it remain limited. Timetabling optimization is significantly complicated by two factors. First, it exhibits strong interdependencies with subsequent fleet assignment decisions of the airlines. Second, flights’ departure and arrival times are important determinants of passenger connection opportunities, of the attractiveness of each (nonstop or connecting) itinerary, and, in turn, of passengers’ booking decisions. Because of these complicating factors, most existing approaches rely on incremental timetabling. This paper introduces an original integrated optimization approach to comprehensive flight timetabling and fleet assignment under endogenous passenger choice. Passenger choice is captured by a discrete-choice generalized attraction model. The resulting optimization model is formulated as a mixed-integer linear program. This paper also proposes an original multiphase solution approach, which effectively combines several heuristics, to optimize the network-wide timetable of a major airline within a realistic computational budget. Using case study data from Alaska Airlines, computational results suggest that the combination of this paper’s model formulation and solution approaches can result in significant profit improvements as compared with the most advanced incremental approaches to flight timetabling. Additional computational experiments based on several extensions also demonstrate the benefits of this modeling and computational framework to support various types of strategic airline decision making in the context of frequency planning, revenue management, and postmerger integration.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
JD发布了新的文献求助10
刚刚
刚刚
恭喜完成签到,获得积分10
刚刚
完美世界应助约翰与蓝侬采纳,获得10
刚刚
caofan发布了新的文献求助10
1秒前
千富的丰柳完成签到,获得积分10
2秒前
2秒前
ReEscort发布了新的文献求助10
2秒前
2秒前
2秒前
2秒前
3秒前
3秒前
打打应助森鹿采纳,获得30
3秒前
大模型应助lee采纳,获得10
3秒前
3秒前
爆米花应助王彤彤采纳,获得10
4秒前
滕隐完成签到 ,获得积分10
4秒前
gong完成签到,获得积分10
4秒前
ding应助hana采纳,获得30
4秒前
Danboard发布了新的文献求助10
5秒前
morning发布了新的文献求助10
5秒前
高雅的菠菜完成签到,获得积分10
6秒前
覃雅丽发布了新的文献求助10
7秒前
初景应助咲李采纳,获得30
7秒前
科研dog发布了新的文献求助10
7秒前
7秒前
8秒前
今后应助认真卿采纳,获得10
8秒前
8秒前
8秒前
孤海未蓝完成签到,获得积分10
8秒前
王121发布了新的文献求助10
9秒前
香蕉觅云应助余生采纳,获得10
10秒前
小蘑菇应助nguyenhai2005采纳,获得10
10秒前
zileepp发布了新的文献求助10
10秒前
11秒前
首歌完成签到,获得积分10
12秒前
12秒前
怕黑冰烟完成签到 ,获得积分10
12秒前
高分求助中
Markov Chain Monte Carlo 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Advanced Weaponeering Fourth Edition, Volume 2 1000
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
Data book on fatigue strength of metallic materials 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7561492
求助须知:如何正确求助?哪些是违规求助? 9142259
关于积分的说明 19545310
捐赠科研通 7149476
什么是DOI,文献DOI怎么找? 3261906
关于科研通互助平台的介绍 2428317
邀请新用户注册赠送积分活动 2251383