Browsing by Author "Delgado, Felipe"

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    Aircraft line maintenance scheduling and optimisation
    (2020) Shaukat, Syed; Katscher, Mathias; Wu, Cheng-Lung; Delgado, Felipe; Larrain, Homero
    With the advent of new technologies and more modern aircraft, many of the maintenance jobs traditionally scheduled for periodic block checks can now be performed in the "line maintenance" environment, i.e., during layovers between scheduled flights of an aircraft. This flexibility can be exploited to reduce maintenance costs and improve fleet utilisation of an airline. In this paper we introduce and study the Line Maintenance Scheduling Problem (LMSP). The LMSP assigns jobs to available maintenance opportunities, defined by aircraft routes, and sets the starting time for each job. Its objective is to minimise the deviation from this schedule with respect to given due dates for each task, without exceeding resource capacity at the airports at any moment. We formulate the LMSP as a mixed integer programming problem, and describe and compare two solution approaches for this problem: an integrated exact solution algorithm, which solves job assignment and timetabling simultaneously, and a sequential, heuristic approach. We tested our algorithms on a set of instances inspired on data provided by an industry partner. Our experiments show the applicability of both approaches on realistic settings: the exact approach was able to find the optimal solution for all instances, in less than 10 min on average. Our analysis also shows with an example that line maintenance can be more efficient when capacity is spatially spread, even if the total capacity is reduced.
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    Dynamic Multiline Vehicle Dispatching Strategy in Transit Operations
    (2022) Delgado, Felipe
    Providing regularity in buses' operation in high-frequency services is essential to offer a good quality of service to users. If buses are not dispatched at regular headways from the terminal, headway irregularity will gradually increase along the line. In this work, we study a vehicle dispatching problem in which multiple lines start their operations from a common terminal where buses can interchange between lines. The model simultaneously decides the ideal dispatching headway for each line and assigns the following arriving buses to the terminal its line to operate and its corresponding dispatching time. The objective is to minimize the dispatching interval's deviation from an ideal headway that is dynamically updated based on the system's status. We formulate our problem as a Mixed-integer quadratic problem and adopt a rolling horizon policy to cope with the dynamic and stochastic environment of public transit systems. We prove that a bus assignment that satisfies the FIFO discipline is an optimal solution for the proposed problem. We evaluate our model in a simulation environment under different operational conditions and study the incremental benefits of allowing different flexibility schemes. Our results show that a full flexibility scheme where buses can freely interchange between lines reduces the coefficient of variation of dispatch headways and improves frequency compliance by nearly 20% when compared with the case where buses are restricted to operate in a single line. It also outperforms a myopic heuristic that adopts a a priori target headway. Computational times are compatible with real-time applications.
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    Dynamic Optimization for Airline Maintenance Operations
    (INFORMS, 2020) Lagos, Carlos; Delgado, Felipe; Klapp, Mathias A.
    The occurrence of unexpected aircraft maintenance tasks can produce expensive changes in an airline's operation. When it comes to critical tasks, it might even cancel programmed flights. Despite this, the challenge of scheduling aircraft maintenance operations under uncertainty has received limited attention in the scientific literature. We study a dynamic airline maintenance scheduling problem, which daily decides the set of aircraft to maintain and the set of pending tasks to execute in each aircraft. The objective is to minimize the expected costs of expired maintenance tasks over the operating horizon. To increase flexibility and reduce costs, we integrate maintenance scheduling with tail assignment decisions. We formulate our problem as a Markov decision process and design dynamic policies based on approximate dynamic programming, including value function approximation, rolling horizon techniques, and a hybrid policy between the latter two that deliversthebest results. In a casestudy based on LATAM airline, we show the value of dynamic optimization by testing our best policies against a simple airline decision rule and a deterministic relaxation with perfect future information. We suggest to schedule tasks requiring less resources first to increase utilization of residual maintenance capacity. Finally, we observe strong economies of scale when sharing maintenance resources between multiple airlines.
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    Impact of omitted variable and simultaneous estimation endogeneity in choice-based revenue management systems
    (2024) Fukushi, Mitsuyoshi; Delgado, Felipe; Raveau, Sebastian
    The demand models used in revenue management systems applied to air transport are affected by endogeneity. This effect is particularly important in the Discrete Choice Models used in Choice Based Revenue Management (CBRM). Still, the sources and the magnitude of the problem have not been completely studied. In this study, we use simulations to analyze the effect of endogeneity in CBRM air transport applications. We replicate different conditions that generate endogeneity described in the literature: the omission of explanatory variables in the behavioral model and the simultaneous determination between fares and demand. On the one hand, results show that simultaneous determination endogeneity is not a concern if the behavioral model includes complete information of the process, without omitting variables. On the other hand, endogeneity affects the estimation and application of CBRM when variables are omitted, a situation that worsens when the omission of variables is combined with the simultaneous determination between fares and demand. Based on these results, we discuss some practical implications and derive some recommendations for the use of CBRM in air transport.