Airlines adjust their flight schedules to satisfy more stringent airport capacity constraints caused by inclement weather or other unexpected disruptions.The problem will be more important and complicated if uncertain...Airlines adjust their flight schedules to satisfy more stringent airport capacity constraints caused by inclement weather or other unexpected disruptions.The problem will be more important and complicated if uncertain disruptions occur in hub airports.A two-stage stochastic programming model was established to deal with the realtime flight schedule recovery and passenger re-accommodation problem.The first-stage model represents the flight re-timing and re-fleeting decision in current time period when capacity information is deterministic,while the second-stage recourse model evaluates the passenger delay given the first-stage solutions when one future scenario is realized.Aiming at the large size of the problem and requirement for quick response,an algorithmic framework combining the sample average approximation and heuristic method was proposed.The computational results indicated of that the proposed method could obtain solutions with around 5% optimal gaps,and the computing time was linearly positive to the sample size.展开更多
基金supported by the National Natural Science Foundation of China(Nos.61079014,71171111)the Funding of Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics(No.BCXJ1314)the Funding of Jiangsu Innovation Program for Graduate Education(No.CXZZ13_0174)
文摘Airlines adjust their flight schedules to satisfy more stringent airport capacity constraints caused by inclement weather or other unexpected disruptions.The problem will be more important and complicated if uncertain disruptions occur in hub airports.A two-stage stochastic programming model was established to deal with the realtime flight schedule recovery and passenger re-accommodation problem.The first-stage model represents the flight re-timing and re-fleeting decision in current time period when capacity information is deterministic,while the second-stage recourse model evaluates the passenger delay given the first-stage solutions when one future scenario is realized.Aiming at the large size of the problem and requirement for quick response,an algorithmic framework combining the sample average approximation and heuristic method was proposed.The computational results indicated of that the proposed method could obtain solutions with around 5% optimal gaps,and the computing time was linearly positive to the sample size.
