Robust airline schedule design in a dynamic scheduling environment

In the past decade, major airlines in the US have moved from banked hub-and-spoke operations to de-banked hub-and-spoke operations in order to lower operating costs. In Jiang and Barnhart (2009), it is shown that dynamic airline scheduling, an approach that makes minor adjustments to flight schedules in the booking period by re-fleeting and re-timing flight legs, can significantly improve utilization of capacity and hence increase profit. In this paper, we develop robust schedule design models and algorithms to generate schedules that facilitate the application of dynamic scheduling in de-banked hub-and-spoke operations. Such schedule design approaches are robust in the sense that the schedules produced can more easily be manipulated in response to demand variability when embedded in a dynamic scheduling environment. In our robust schedule design model, we maximize the number of potentially connecting itineraries weighted by their respective revenues. We provide two equivalent formulations of the robust schedule design model and develop a decomposition-based solution approach involving a variable reduction technique and a variant of column generation. We demonstrate, through experiments using data from a major U.S. airline that the schedule generated can improve profitability when dynamic scheduling is applied. It is also observed that the greater the demand variability, the more profit our robust schedules achieve when compared to existing ones

Online scheduling: a survey

In this article a deep search of the literature of online scheduling is conducted. This paper intends to assess the developments and solutions found for online scheduling problems. Online scheduling is a very important topic since most of the real scheduling problems have dynamic characteristics. First, it was developed a literature review about scheduling problems, dividing them in stochastic and deterministic problems as well as in online and offline problems. Then, a bibliometric analysis was performed. Finally, some case studies in the field of online scheduling were analyzed. Online Scheduling is mostly explored in industry and health areas. In some articles explored there is a rescheduling, and the sequence of task may change due to the arrival of new tasks. In other cases, the new tasks are introduced in blocks of time that do not affect the previous schedule. This last technique is limited, since, with the arrival of new tasks, the schedule is not re-evaluated. Therefore, it is thought that, in future work, within the scope of online scheduling, when new tasks or other significant changes enter the system, the system should be evaluated, allowing the necessary changes to be made to the existing schedule. The Industry 4.0 and the evolution of Internet of Things (IoT), Deep Learning and Machine Learning favours a continuous and real-time flow of information, which allows the implementation of real-time online scheduling. This is a branch that should be explored in future works.FCT - Fundação para a Ciência e a Tecnologia(UIDB/00319/2020

Aircraft Maintenance Routing Problem – A Literature Survey

The airline industry has shown significant growth in the last decade according to some indicators such as annual average growth in global air traffic passenger demand and growth rate in the global air transport fleet. This inevitable progress makes the airline industry challenging and forces airline companies to produce a range of solutions that increase consumer loyalty to the brand. These solutions to reduce the high costs encountered in airline operations, prevent delays in planned departure times, improve service quality, or reduce environmental impacts can be diversified according to the need. Although one can refer to past surveys, it is not sufficient to cover the rich literature of airline scheduling, especially for the last decade. This study aims to fill this gap by reviewing the airline operations related papers published between 2009 and 2019, and focus on the ones especially in the aircraft maintenance routing area which seems a promising branch

Collaborative rescheduling of flights in a single mega-hub network

Traditionally, airlines have configured flight operations into a Hub and Spoke network design. Using connecting arrival departure waves at multiple hubs these networks achieve efficient passenger flows. Recently, there has been much growth in the development of global single mega-hub (SMH) flight networks that have a significantly different operating cost structure and schedule design. These are located primarily in the Middle East and are commonly referred to as the ME3. The traditionalist view is that SMH networks are money losers and subsidized by sovereign funds. This research studies and analyzes SMH networks in an attempt to better understand their flight efficiency drivers. Key characteristics of SMH airports are identified as: (i) There are no peak periods, and flight activity is balanced with coordinated waves (ii) No priority is assigned to arrival/departure times at destinations (selfish strategy) only hub connectivity is considered (iii) There is less than 5% OD traffic at SMH (iv) The airline operates only non-stop flights (v) Passengers accept longer travel times in exchange for economic benefits (vi) Airline and airport owners work together to achieve collaborative flight schedules. This research focuses on the network structure of SMH airports to identify and optimize the operational characteristics that are the source of their advantages. A key feature of SMH airports is that the airline and airport are closely aligned in a partnership. To model this relationship, the Mega-Hub Collaborative Flight Rescheduling (MCFR). Problem is introduced. The MCFR starts with an initial flight schedule developed by the airline, then formulates a cooperative objective which is optimized iteratively by a series of reschedules. Specifically, in a network of iEM cities, the decision variables are i* the flight to be rescheduled, Di* the new departure time of flight to city i* and Hi* the new hold time at the destinatioin city i*. The daily passenger traffic is given by Ni,j and normally distributed with parameters µNi,j and sNi,j. A three-term MCFR objective function is developed to represent the intersecting scheduling decision space between airlines and airports: (i) Passenger Waiting Time (ii) Passenger Volume in Terminal, and (iii) Ground Activity Wave Imbalance. The function is non-linear in nature and the associated constraints and definitions are also non-linear. An EXCEL/VBA based simulator is developed to simulate the passenger traffic flows and generate the expected cost objective for a given flight network. This simulator is able to handle up to an M=250 flight network tracking 6250 passenger arcs. A simulation optimization approach is used to solve the MCFR. A Wave Gain Loss (WGL) strategy estimates the impact Zi of flight shift Δi on the objective. The WGL iteratively reschedules flights and is formulated as a non-linear program. It includes functions to capture the traffic affinity driven solution dependency between flights, the relationship between passengers in terminal gradients and flight shifts, and the relationship between ground traffic activity gradients and flight shifts. Each iteration generates a Zi ranked list of flights. The WGL is integrated with the EXCEL/VBA simulator and shown to generate significant costs reduction in an efficient time. Extensive testing is done on a set of 5 flight network problems, each with 3 different passengers flow networks characterized by low, medium and high traffic concentrations

Programació dinàmica de vols atenent a demandes estocàstiques

La programació de vols és una de les principals activitats de planificació que es duen a terme en una companyia aèria; el resultat d'aquesta tasca té implicacions que transgredeixen l'àmbit operacional i esdevé un factor determinant de cara a millorar la competitivitat en el sector del transport aeri. Sovint, la naturalesa estratègica d'aquesta activitat implica que es realitzi a una antelació en què la previsió respecte la demanda de passatgers és força difusa i pot resultar, el dia d'operació dels vols, en manques d'eficiència al deixar vols amb seients buits i a l'haver-ne assignat d'altres amb avions de massa poca capacitat. Així doncs, en aquest projecte es presenta una metodologia (algoritme DACRA) que executant petites alteracions sobre la planificació de vols inicial, realitza ajustaments de capacitat, possibilitant l'adaptació contínua del programa de vols a les actualitzacions disponibles respecte la previsió de demanda de passatgers per a una data concreta, tot millorant-ne els beneficis operatius i preservant que les noves solucions generades siguin operativament factibles