Multiple-Allocation Hub-and-Spoke Network Design With Maximizing Airline Profit Utility in Air Transportation Network

被引:2
作者
Yu, Nan [1 ]
Dong, Bin [1 ]
Qu, Yuben [2 ,3 ]
Zhang, Mingwei [1 ]
Chen, Guihai [4 ]
Tan, Qingqing [1 ]
Wang, Yanyan [5 ]
Dai, Haipeng [4 ]
机构
[1] State Key Lab Air Traff Management Syst, Nanjing 210022, Peoples R China
[2] Nanjing Univ Aeronaut & Astronaut, Key Lab Dynam Cognit Syst Electromagnet Spectrum S, Minist Ind & Informat Technol, Nanjing 211106, Peoples R China
[3] Nanjing Univ Aeronaut & Astronaut, Coll Elect & Informat Engn, Nanjing 211106, Peoples R China
[4] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210023, Peoples R China
[5] Hohai Univ, Coll Comp & Informat, Nanjing 211100, Peoples R China
基金
中国国家自然科学基金;
关键词
Airline industry; Transportation; Routing; Costs; Approximation algorithms; Resource management; Airports; Airline profit; cardinality; transportation profit utility; hub location problem; approximation algorithm; submodular set function; greedy algorithm; customer preference; routing allocation mode; MARGINAL UTILITY; BENDERS DECOMPOSITION; LOCATION PROBLEM; COVERING PROBLEM; MEDIAN PROBLEM; SINGLE; ECONOMIES; ALGORITHMS; MODELS; SCALE;
D O I
10.1109/TITS.2023.3348466
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Airlines commonly need to take into consideration maximizing their profit while designing the hub-and-spoke network to obtain more market share and promote healthy development of aviation industry. Hence, in this article, we study the problem of multiple-allocation HUb and spoke network design for ROuting flight flows to maximize airline profit utility (HURO). That is, given a set of airport nodes, a set of flight flows with known origin positions and destination positions, finding a limited number of hub edges to transfer flows and determining routing allocation mode considering customer preference such that the overall transportation profit utility is maximized. To address HURO problem, we first consider a relaxed version of HURO (HURO-R for short). We prove that HURO-R falls into the realm of maximizing a submodular set function subject to a cardinality constraint, and propose an algorithm with a constant approximation ratio. Next, we design a two-level algorithm framework with a constant approximation ratio to address HURO. Besides, we consider variants of HURO, HURO-C and HURO-RU, and design approximation algorithms to address them. We conduct simulation experiments on standard dataset and field experiments to verify our theoretical findings. The results shows that our proposed algorithm can outperform other comparison algorithms by 75.28 percent.
引用
收藏
页码:7294 / 7310
页数:17
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