Optimization Approaches to the Single Airport Ground-Holding Problem

Abstract

This paper surveys optimization approaches to the single airport ground-holding problem. The article provides a comprehensive summary of six approaches, highlights the merits and limitations of each, and compares the performance of four models over a large range of cost functions. The first sequential evaluation model for the single airport ground-holding problem is introduced. Motivated by current practice in Collaborative Decision Making planning under Collaborative Decision Making, the sequential model evaluates a method of choosing planned airport acceptance rates. The evaluator is used to compare the performance of a static model applied iteratively to traditional dynamic models and to evaluate the performance of a static model with a limited look-ahead horizon. The findings suggest that research on the single airport ground-holding problem has focused either on developing high-performance complex dynamic models whose outputs are not consistent with current practice or static models that perform less well in theory but can incorporate operational considerations. The experiments show that dynamic models outperform static models by a large margin in simulation but that the performance gap can be reduced by limiting the look-ahead horizon of a static model, which allows it to imitate the ability of a dynamic model to “wait and see.” The models were evaluated using real arrival and departure schedules from San Francisco International Airport.