Browsing by Subject "chance constraints"

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    Fleet type assignment and robust airline scheduling with chance constraints under environmental emission considerations
    (2013) Şafak, Özge
    Fleet Type Assignment and Robust Airline Scheduling is to assign optimally aircraft to paths and develop a flight schedule resilient to disruptions. In this study, a Mixed Integer Nonlinear Programming formulation was developed using controllable cruise time and idle time insertion to ensure passengers’ connection service level with the objective of minimizing the costs of fuel consumption, CO2 emissions, idle time and spilled passengers. The crucial contribution of the model is to take fuel efficiency of aircraft into considerations to compensate for the idle time insertion as well as the cost of spilled passengers due to the insufficient seat capacity. The nonlinearity in the fuel consumption function associated with controllable cruise time was handled by second order conic reformulations. In addition, the uncertainty coming from a random variable of non-cruise time arises in chance constraints to guarantee passengers’ connection service level, which was also tackled by transforming them into conic inequalities. We compared the performance of the schedule generated by the proposed model to the published schedule for a major U.S. airline. On the average, there exists a 20% total cost saving compared to the published schedule. To solve the large scale problems in a reasonable time, we also developed a two-stage algorithm, which decomposes the problem into planning stages such as fleet type assignment and robust schedule generation, and then solves them sequentially.
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    Robust airline scheduling with controllable cruise times and chance constraints
    (2012) Duran, Aslıgül Serasu
    This is a study on robust airline scheduling where flight block times are considered in two parts as cruise time and non-cruise time. Cruise times are controllable and non-cruise times are random variables. Cruise time controllability is used together with idle time insertion to handle uncertainty to guarantee passenger connection service levels while ensuring minimum costs. The nonlinearity of these cost functions are handled by representing them via second order conic inequalities. The uncertainty in non-cruise times are modeled through chance constraints on passenger connection service levels, which are expressed using second order conic inequalities using the closed form equations. Congestion levels of origin and destination airports are used to decide variability for each flight. Computational study shows exact solutions can be obtained by commercial solvers in seconds for a single hub schedule and in minutes for a 4-hub daily schedule of a major US carrie