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Game-theoretic analysis of the impact of crew overnight hotel cost on airlines' fleet assignment and crew pairing

JOURNAL OF AIR TRANSPORT MANAGEMENT 2023年 113卷

作者： Ding, Chengjin Chen, Xinyuan Wu, Weiwei Wei, Wenbin Xin, Zelin Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat Nanjing 210016 Peoples R China San Jose State Univ Coll Engn Dept Aviat & Technol One Washington Sq San Jose CA 95192 USA Nanjing Univ Aeronaut & Astronaut Coll Sci Nanjing 210016 Peoples R China

Crew costs account for a high proportion of the total operational costs of an airline. The cost of overnight stay for the crew at a hotel is an important additional cost. To address this problem, this study establishes an integrated model to depict the interaction between the fleet assignment problem and the crew pairing problem. Because this cost is largely determined by the price agreed by the agreement hotel group, we further present a Stackelberg price game model to capture the interdependence between the integrated fleet assignment and crew pairing of airlines and the price game among hotel groups that provide accommodation services for airlines. We combine the idle time re-allocation with a spatio-temporal graph convolutional network to ensure the robustness of crew pairing. The solvability of the model is improved using the Reformulation-Linearization Technique. To obtain the overall Nash equilibrium of the Stackelberg price game model, we design a heuristic algorithm based on a decomposition algorithm and a proximity search algorithm. A case study is made to demonstrate that our robust model is cost-saving for the airline.

关键词： Crew pairing fleet assignment Stackelberg price game Reformulation linearization technique Idle time re-allocation

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Robust Model for fleet assignment with Station Purity and Robust Opportunities 2021

Robust Model for Fleet Assignment with Station Purity and Ro...

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2021 The 9th International Conference on Information Technology: IoT and Smart City

作者： Chengjin Ding Yuzhen Guo Jingxue Weng College of Science Nanjing University of Aeronautics and Astronautics China College of Economics and Management Nanjing University of Aeronautics and Astronautics China

ISBN: (纸本)9781450384971

Irregular flights in airline operations annually result in billions of dollars of additional costs to airlines. Airlines strive to mitigate these costs by creating schedules that can better withstand disruptions. We know that fleet assignment problem (FAP) considering only economy will lead to the inability of aircraft routing problem (ARP) and crew pairing problem (CPP) to absorb disruptions. In order to carry out robust fleet assignment, we established a model of FAP considering not only station purity which increase the opportunities of finding a move-up aircraft and crew in recover, but also feasible flight string which is found through a model to absorb delays. We can create robust opportunities by assigning constraints. Next, we preprocessed the delay time of each flight by a designed neural network. Validity of the model was verified by the data of a France airlines. The robust model can significantly reduce the delay of aircrafts about 20.75% and crews about 16.7%.

关键词： Robust Planning fleet assignment Absorption of disruptions Station purity

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A new approach to fleet assignment and aircraft routing problems

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Transportation Research Procedia 2021年 59卷 67-75页

作者： Yusuf Ziya Unal Mehmet Sevkli Ozgur Uysal Ali Turkyilmaz Faculty of Engineering Istanbul University-Cerrahpasa Istanbul 34320 Turkey Farmer School of Business Miami University Oxford OH 45056 USA College of Engineering and Technology American University of the Middle East Dasman 26666 Kuwait School of Engineering and Digital Sciences Nazarbayev University Nur-Sultan 010000 Kazakhstan

In this study, a new mathematical formulation is developed for fleet scheduling problems (i.e., the combination of fleet assignment and aircraft routing problems) in single hub & spoke systems. The proposed model aims to minimize the total cost of allocating aircraft to flights while observing the sequence of flights to be subject to seat capacity, passenger demand, aircraft availability, and overlapping flights. Since the classical fleet scheduling problem is NP-hard, a couple of complexity reduction techniques are developed. Thus, the size of the problem is decreased significantly. To evaluate the model’s performance, it is implemented to an airline carrier with 170 aircraft and 1290 (645 round trip) flights. As a result, the proposed method ended up with an improvement of 36.7% for a 2-day planning horizon.

关键词： fleet scheduling fleet assignment aircraft routing linear programming

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fleet & tail assignment under uncertainty

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DISCRETE OPTIMIZATION 2024年 52卷

作者： Glomb, Lukas Liers, Frauke Roesel, Florian FAU Erlangen Nuremberg Dept Data Sci Cauerstr 11 D-91058 Erlangen Germany FAU Erlangen Nuremberg Dept Math Cauerstr 11 D-91058 Erlangen Germany

Airlines solve many different optimization problems and combine the resulting solutions to ensure smooth, minimum-cost operations. Crucial problems are the fleet assignment, which assigns aircraft types to flights of a given schedule, and the Tail assignment, which determines individual flight sequences to be performed by single aircraft. In order to find a cost-optimal solution, many airlines use mathematical optimization models. For these to be effective, the available data and forecasts must reflect the situation as accurately as possible. However, especially in times of a pandemic, the underlying plan is subject to severe uncertainties: Staff and demand uncertainties can even lead to flight cancellations or result in entire aircraft having to be grounded. Therefore, it is advantageous for airlines to protect their mathematical models against uncertainties in the input parameters. In this work, two computational tractable and cost-efficient robust models and solution approaches are developed: First, we set up a novel mixed integer model for the integrated fleet and tail assignment, which ensures that as few subsequent flights as possible have to be canceled in the event of initial flight cancellations. We then solve this model using a procedure that ensures that the costs of the solution remain considerably low. Our second model is an extended fleet assignment model that allows us to compensate for entire aircraft cancellations in the best possible way, taking into account rescheduling options. We demonstrate the effectiveness of both approaches by conducting an extensive computational study based on real flight schedules of a major German airline. It turns out that both models deliver stable, cost-efficient solutions within less than ten minutes, which significantly reduce follow-up costs in the case uncertainties arise.

关键词： Mixed integer programming Robust optimization fleet assignment Tail assignment

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Novel approach to deal with demand volatility on fleet assignment models

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JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY 2018年第6期69卷 895-904页

作者： Boudia, Mourad Delahaye, Thierry Gabteni, Semi Acuna-Agost, Rodrigo Amadeus SAS Innovat & Res Div Sophia Antiplos France

One of the important applications of operations research in the airline industry is fleet assignment. The problem is posed as an assignment of aircraft capacity to flight legs at the planning level, in general one year before departure date. The fleet assignment problem comes after schedule design and without any influence on it. Even if the schedule is defined by a set of flight legs, the source of revenues for airlines is itineraries, many of which have more than one leg. Existing research is based on the itinerary-based fleet assignment model (IFAM) that captures the network effects. Nevertheless, the difficulty of forecasting itinerary demand prevents the widespread implementation in the airline industry of the IFAM and impacts heavily on its performance. This paper proposes a new model based on itinerary grouping. Our itinerary group fleet assignment model (IGFAM) deals with the difficulties caused by itinerary forecast by replacing them with aggregated demand forecasts. We conduct comparisons between models, considering their respective profit based on real-life demand using a simulation framework. Though the comparison is conservative, it still leads to the new model delivering an advantage in almost all circumstances. The greatest benefits are observed at the highest demand volatility.

关键词： fleet assignment airlines clustering passenger mix model

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An integrated flight scheduling and fleet assignment problem under uncertainty

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COMPUTERS & OPERATIONS RESEARCH 2018年 100卷 333-342页

作者： Kenan, Nabil Jebali, Aida Diabat, Ali New York Univ Abu Dhabi Div Engn Abu Dhabi 129188 U Arab Emirates Univ Paris Est ESIEE Paris Dept Ingn Syst 2 Blvd Blaise PascalCite DECARTES BP 99 F-93162 Noisy Le Grand France NYU Dept Civil & Urban Engn Tandon Sch Engn Brooklyn NY 11201 USA

Flight scheduling and fleet assignment are the two most prominent decisions in airline planning as they contribute toward a majority of the costs and revenues of an airline company. Moreover, these decisions have to be made 10-12 weeks prior to the flight date as mandated by labor unions in order to accommodate cabin crew scheduling requirements. Since demand and fares are highly uncertain, a two-stage stochastic programming model was developed for flight scheduling and fleet assignment where the fleet family assigned to each scheduled flight leg is decided at the first-stage. Then, the fleet type to assign to each flight leg is decided at the second-stage based on demand and fare realization. Sample average approximation (SAA) algorithm is then used to solve the problem and provide information on the quality of the solution. To the extent of our knowledge, this work is the first to apply the SAA algorithm to the airline industry. Experiments conducted on a case study based on a flight network of a legacy airline company show that modeling the stochastic problem with 100 scenarios is sufficient to capture the effect of demand and fare uncertainty and to provide a solution with an optimality gap less than 1% within a reasonable computational time. A sensitivity analysis on different parameters of the model was also carried out and points out the applicability of the proposed model and solution in practice. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Flight scheduling fleet assignment Stochastic demand Stochastic fares Sample average approximation

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Variable Neighborhood Search to solve an airline fleet sizing and fleet assignment problem

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Transportation Research Procedia 2019年 37卷 258-265页

作者： Slavica Dožić Ana Jelović Milica Kalić Mirjana Čangalović University of Belgrade Faculty of Transport and Traffic Engineering 305 Vojvode Stepe Street Belgrade 11000 Serbia University of Belgrade Faculty of Organizational Sciences 154 Jove Ilića Street Belgrade 11000 Serbia

In order to enable an airline to realize its planned schedule to and perform successfully, it is very important to determine the fleet size in an appropriate way. fleet size represents the number of aircraft in an airline’s fleet. Larger number of aircraft than it is required means lower fleet utilization, which further affects increase of costs. Lower number of aircraft than it is required means spill of demand, i.e. reallocation of passengers to competitors’ flights and missing out on the opportunity to make profit. The problem considered in this paper refers to fleet size and fleet assignment in the case of single fleet (only one type of aircraft). In order to solve the problem we proposed a metaheuristic approach based on the Variable Neighborhood Search (VNS) methodology, which solves both fleet sizing problem and fleet assignment problem simultaneously. Preliminary numerical results based on real data are compared to optimal solution obtained by CPLEX and show the validity of the proposed modelling approach.

关键词： fleet Sizing fleet assignment Metaheuristic Variable Neighborhood Search

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Solving a large-scale integrated fleet assignment and crew pairing problem

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ANNALS OF OPERATIONS RESEARCH 2017年第1期253卷 477-500页

作者： Ozener, Okan Orsan Matoglu, Melda Ormeci Erdogan, Gunes Haouari, Mohamed Sozer, Hasan Ozyegin Univ Sch Engn Istanbul Turkey Univ New Hampshire Peter T Paul Coll Business & Econ Durham NH 03824 USA Univ Bath Sch Management Bath BA2 7AY Avon England Qatar Univ Dept Mech & Ind Engn Coll Engn Doha Qatar

Airline schedule planning problems are typically decomposed into smaller problems, which are solved in a sequential manner, due to the complexity of the overall problems. This results in suboptimal solutions as well as feasibility issues in the consecutive phases. In this study, we address the integrated fleet assignment and crew pairing problem (IFACPP) of a European Airline. The specific network and cost structures allow us to develop novel approaches to this integrated problem. We propose an optimization-driven algorithm that can efficiently handle large scale instances of the IFACPP. We perform a computational study on real-world monthly flight schedules to test the performance of our solution method. Based on the results on instances with up to 27,500 flight legs, we show that our algorithm provides solutions with significant cost savings over the sequential approach.

关键词： fleet assignment Crew pairing Airline operations planning Large-scale neighborhood search

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An integrated flight scheduling and fleet assignment method based on a discrete choice model

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COMPUTERS & INDUSTRIAL ENGINEERING 2016年第0期98卷 195-210页

作者： Zhang Dong Yu Chuhang Lau, H. Y. K. Henry Univ Hong Kong Room 8-23Haking Wong Bldg Hong Kong Hong Kong Peoples R China Univ Hong Kong Room 8-15Haking Wong Bldg Hong Kong Hong Kong Peoples R China

The airline industry is capital intensive and operates on a thin profit margin. Optimal and flexible flight schedule is essential for airlines to survive in such competitive market. In this study, we focus on the integrated flight scheduling and fleet assignment problem based on a discrete choice model. Two mixed integer programming models are proposed: the first model solves the integrated flight scheduling and fleet assignment problem and the second model further considers the itinerary price elasticity. A heuristic algorithm is also proposed to efficiently solve the second model. In numerical studies, a micro market is simulated to evaluate the performance of our proposed models and algorithms. Experimental results reveal that our models can achieve a significant profit improvement under a reasonable computation time. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Flight scheduling fleet assignment Discrete choice model Integrated scheduling

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Destination selection and flight scheduling for regional airlines at slot-constrained airports

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2025年第3期32卷 1400-1421页

作者： Santini, Alberto Univ Pompeu Fabra Dept Econ & Business Carrer Ramon Trias Fargas 25-57 Barcelona 08005 Spain Barcelona Sch Econ Data Sci Ctr Carrer Ramon Trias Fargas 25-57 Barcelona 08005 Spain

We present the problem of a regional airline based at a slot-constrained airport, which must select a set of destinations to serve, how many flights per day to operate to each destination, at what time the flights take place and which aircraft operates each flight. Restricting ourselves to the special case of regional airlines, which fly round trips from a central hub, we are able to tackle the four above decisions jointly. By contrast, in the existing literature, these decisions are usually optimised separately for generic airline networks. To solve the proposed problem, we introduce two compact integer formulations: a three-index and a two-index formulation. This latter, however, only solves a relaxation of the original problem because it cannot guarantee that all constraints are respected. Therefore, we embed the two-index formulation into an iterative algorithm which dynamically adds violated constraints. Computational experiments highlight the validity of this approach and provide insights into the characteristics of the solutions.

关键词： airline optimisation destination selection fleet assignment tail assignment

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