Browsing by Subject "Cruise time controllability"

Now showing 1 - 6 of 6

Open Access
Airline rescheduling with aircraft unavailability period
(2019-06) Yetimoğlu, Yücel Naz
Airlines design their initial schedules under the assumption that all resources will be available on time and ights will operate as planned. However, some disruptions occur due to mechanical failures and unexpected delays of maintenance, making the aircraft unavailable for a certain period of time. These deviations from the initial plan result in high operational costs in addition to the serious inconveniences experienced by passengers. In the literature, it is a common practice to develop sequential approaches at which aircraft and passenger recovery problems are consecutively handled. In this study, we address them simultaneously and propose an integrated math-heuristic framework with an aim to maximize the profit of the airline. In the first phase, we develop a nonlinear mixed integer optimization model for aircraft recovery and utilize conic programming approach to mitigate computational difficulty. We incorporate cancellation and re-routing decisions for ights utilizing cruise time controllability which results in nonlinear fuel burn and CO2 emission cost functions. In the second phase, we develop a passenger recovery algorithm that makes individual itinerary based recovery decisions under the seat capacity restrictions and provide realistic cancellation cost formulations. Lastly, we propose an integrated search algorithm to maintain the integration between two phases through fixing assignment variables in the first phase. We compare the performance of the proposed algorithm to the base policy where all disrupted ights are directly cancelled. We observe improvements in terms of profit and the number of overnight passengers.
Open Access
Airline scheduling to minimize operational costs and variability
(2021-08) Şimşek, Deniz
Airlines tend to design their ﬂights schedules with the primary concern of the minimization of operational costs. However, the recently emerging idea of resilient scheduling deﬁned as staying operational in case of unexpected disruptions and adaptability should be of great importance for airlines as well due to the high opportunity costs caused by the ﬂight cancellations and passenger inconvenience caused by delays in the schedule. In this study, we integrate resilient airline schedule design, aircraft routing and ﬂeet assignment problems with uncertain non-cruise times and controllable cruise times. We follow a data-driven method to estimate ﬂight delay probabilities to calculate the airport congestion coeﬃcients required for the probability distributions of non-cruise time random variables. We formulate the problem as a bi-criteria nonlinear mixed integer mathematical model with chance constraints. The nonlinearity caused by the fuel consumption and CO2 emission function associated with the controllable cruise times in our ﬁrst objective is handled by second order conic inequalities. We minimize the total absolute deviation of the aircraft path variabilities from the average in our second objective to generate balanced schedules in terms of resilience. We follow an ε-constraint approach to scalarize and solve our problem via commercial solvers and we also devise a discretized approximation and search algorithm to solve large instances. We compare the recovery performances of our proposed schedules to the minimum cost schedules by a scenario-based posterior analysis. As a key contribution, we show that in the schedule generation phase, designing resilient schedules by allowing them to deviate from the minimum cost within the trade-oﬀ between the operational costs and the variability, the potential recovery costs in case of unexpected disruptions can be reduced signiﬁcantly.
Open Access
Integrated aircraft-path assignment and robust schedule design with cruise speed control
(Elsevier, 2017-08) Şafak, Ö.; Gürel, S.; Aktürk, M. S.
Assignment of aircraft types, each having different seat capacity, operational expenses and availabilities, critically affects airlines’ overall cost. In this paper, we assign fleet types to paths by considering not only flight timing and passenger demand, as commonly done in the literature, but also operational expenses, such as fuel burn and carbon emission costs associated with adjusting the cruise speed to ensure the passenger connections. In response to flight time uncertainty due to the airport congestions, we allow minor adjustments on the flight departure times in addition to cruise speed control, thereby satisfying the passenger connections at a desired service level. We model the uncertainty in flight duration via a random variable arising in chance constraints to ensure the passenger connections. Nonlinear fuel and carbon emission cost functions, chance constraints and binary aircraft assignment decisions make the problem significantly more difficult. To handle them, we use mixed-integer second order cone programming. We compare the performance of a schedule generated by the proposed model to the published schedule for a major U.S. airline. On the average, there exists a 20% overall operational cost saving compared to the published schedule. To solve the large scale problems in a reasonable time, we also develop a two-stage algorithm, which decomposes the problem into planning stages such as aircraft-path assignment and robust schedule generation, and then solves them sequentially.
Open Access
An integrated approach for airline scheduling, aircraft fleeting and routing with cruise speed control
(Elsevier, 2016) Gürkan, H.; Gürel, S.; Aktürk, M. S.
To place an emphasis on profound relations among airline schedule planning problems and to mitigate the effect of unexpected delays, we integrate schedule design, fleet assignment and aircraft routing problems within a daily planning horizon while passengers' connection service levels are ensured via chance constraints. We propose a nonlinear mixed integer programming model due to the nonlinear fuel consumption and CO2 emission cost terms in the objective function, which is handled by second order conic reformulation. The key contribution of this study is to take into account the cruise time control for the first time in an integrated model of these three stages of airline operations. Changing cruise times of flights in an integrated model enables to construct a schedule to increase utilization of fuel efficient aircraft and even to decrease total number of aircraft needed while satisfying the same service level and maintenance requirements for aircraft fleeting and routing. There is a critical tradeoff between the number of aircraft needed to fulfill the required flights and overall operational expenses. We also propose two heuristic methods to solve larger size problems. Finally, computational results using real data obtained from a major U.S. carrier are presented to demonstrate potential profitability in applying the proposed solution methods.
Open Access
An integrated approach for robust airline scheduling, aircraft fleeting and routing with cruise speed control
(2014) Gürkan, Hüseyin
To place emphasis on profound relations among airline schedule planning problems and to mitigate the effect of unexpected delays, we integrate robust schedule design, fleet assignment and aircraft routing problems within a daily planning horizon while passengers’ connection service levels are ensured via chance constraints and maintenance requirements are satisfied. We propose a nonlinear mixed integer programming model. In the objective function, the cost functions due to fuel consumption and CO2 emission cost involve nonlinearity. This nonlinearity is handled by second order conic reformulation. The key contribution of this study is to take into account the cruise time control for the first time in an integrated model of these three stages of airline operations. Changing cruise times of flights in an integrated model enables to construct a schedule to increase utilization of efficient aircraft and even to decrease the total number of aircraft needed while satisfying service level and maintenance requirements for aircraft fleeting and routing. Besides, for the robust schedule design problem, it is possible to improve the solution since a routing decision could eliminate the necessity of inserting idle time or compressing cruise time. In addition, we propose two heuristic methods to solve large size problems faster than the integrated model. Eventually, computational results using real data obtained from a major U.S. carrier are presented to demonstrate potential profitability in applying the proposed solution methods.
Open Access
Resilient airline scheduling to minimize delay risks
(Elsevier Ltd, 2022-06-06) Şi̇mşek, D.; Aktürk, M. Seli̇m
Airlines tend to design their flights schedules with the primary concern of the minimization of operational costs. However, the recently emerging idea of resilient scheduling defined as staying operational in case of unexpected disruptions and adaptability should be of great importance for airlines as well due to the high opportunity costs caused by the flight cancellations and passenger inconvenience caused by delays in the schedule. In this study, we integrate resilient airline schedule design, aircraft routing and fleet assignment problems with uncertain non-cruise times and controllable cruise times. We follow a data-driven method to estimate flight delay probabilities to calculate the airport congestion coefficients required for the probability distributions of non-cruise time random variables. We formulate the problem as a bi-criteria nonlinear mixed integer mathematical model with chance constraints. The nonlinearity caused by the fuel consumption and CO2 emission function associated with the controllable cruise times in our first objective is handled by second order conic inequalities. We minimize the total absolute deviation of the aircraft path variability’s from the average in our second objective to generate balanced schedules in terms of resilience. We compare the recovery performances of our proposed schedules to the minimum cost schedules by a scenario-based posterior analysis.