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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
Future发布了新的文献求助10
1秒前
3秒前
4秒前
安详怜蕾发布了新的文献求助10
5秒前
神山识完成签到,获得积分10
9秒前
long发布了新的文献求助10
10秒前
魈玖发布了新的文献求助10
12秒前
xueniaoer发布了新的文献求助20
12秒前
14秒前
Hello应助cyy读研日记采纳,获得10
15秒前
annzl发布了新的文献求助10
16秒前
19秒前
问我关注了科研通微信公众号
20秒前
22秒前
可爱的函函应助核桃采纳,获得10
23秒前
慕青应助核桃采纳,获得10
23秒前
Hello应助核桃采纳,获得10
23秒前
小二郎应助核桃采纳,获得10
23秒前
爆米花应助核桃采纳,获得10
23秒前
希望天下0贩的0应助核桃采纳,获得10
23秒前
24秒前
27秒前
燃烧的火柴完成签到,获得积分10
27秒前
kaustal完成签到,获得积分10
28秒前
29秒前
annzl完成签到,获得积分10
29秒前
29秒前
30秒前
30秒前
希望天下0贩的0应助greentea采纳,获得10
31秒前
32秒前
lwt发布了新的文献求助10
32秒前
33秒前
隐形曼青应助夨坕采纳,获得10
35秒前
麟书夷完成签到 ,获得积分10
35秒前
大个应助猪猪hero采纳,获得10
35秒前
麟书夷关注了科研通微信公众号
38秒前
问我发布了新的文献求助10
39秒前
42秒前
soulking应助无语的电源采纳,获得10
45秒前
高分求助中
【重要!!请各位用户详细阅读此贴】科研通的精品贴汇总(请勿应助) 10000
Genomic signature of non-random mating in human complex traits 2000
Semantics for Latin: An Introduction 1099
醤油醸造の最新の技術と研究 1000
Plutonium Handbook 1000
Three plays : drama 1000
Robot-supported joining of reinforcement textiles with one-sided sewing heads 640
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 4109825
求助须知:如何正确求助?哪些是违规求助? 3648164
关于积分的说明 11555880
捐赠科研通 3353853
什么是DOI,文献DOI怎么找? 1842450
邀请新用户注册赠送积分活动 908867
科研通“疑难数据库(出版商)”最低求助积分说明 825770