Journal
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS
Volume 41, Issue 1, Pages 231-239Publisher
AMER INST AERONAUTICS ASTRONAUTICS
DOI: 10.2514/1.G002964
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This paper introduces a novel stochastic approach for the ground-delay-program planning under uncertainty, using chance-constrained optimization. The major advantage of the chance-constrained model is the ability to provide robust solutions with user-defined service level. The approach is compared with the Ball etal. (''A Stochastic Integer Program with Dual Network Structure and Its Application to the Ground-Holding Problem,'' Operations Research, Vol.51, No.1, Feb.2003, pp. 167-171) model for selecting planned airport acceptance rates for airports in a metroplex, which is an interdependent system in close geographic proximity. The approaches were evaluated using real flight schedules and landing-capacity data from the New York City metroplex airports. Although the Ball etal. model was found to be more efficient, the chance-constrained model shows the ability to provide a quantized way to balance the solution's robustness and potential cost by choosing a proper service level. Moreover, the parallel-computing framework was demonstrated to be helpful in improving the computing efficiency, which suggests that deploying more computing resources would help solve a large-scale planning problem under uncertainty in the same framework.
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