Article ID: | iaor20164358 |
Volume: | 50 |
Issue: | 1 |
Start Page Number: | 132 |
End Page Number: | 149 |
Publication Date: | Feb 2016 |
Journal: | Transportation Science |
Authors: | Hansen Mark, Liu Yi |
Keywords: | combinatorial optimization, vehicle routing & scheduling, stochastic processes, simulation, decision |
This work introduces the goal of predictability into ground delay program (GDP) cost optimization under capacity uncertainty for a single airport case. This is accomplished by modifying traditional GDP delay cost functions so that they incorporate predictability. Extra premiums are assigned to unplanned delays, and planned but unincurred delays, due to their unpredictability. Two stochastic GDP models are developed based on deterministic queueing theory and continuous approximation to estimate the delay components in the cost functions: a static no‐revision model and a dynamic model considering one GDP revision. The decision on the time when the planned airport arrival capacity moves from the low level to the normal level,