Dynamic Departure Pushback Control at Airports: Part A – Linear Penalty-based Algorithms and Policies

Journal: Naval Research Logistics 

Abstract: Airport surface congestion can lead to significantly long taxi-out times, thus resulting in increased fuel-burn costs as well as excessive emissions of greenhouse gases. To curtail this undesirable syndrome, in this paper, the authors propose a new penalty-based dynamic departure pushback control (PDPC) strategy, which employs a linear penalty function dependent not only on the taxiway queue limit but also on the current queue length to ration the pushback frequency at airports, and trades taxiway queueing times with gate-hold delays to minimize the total operational cost (fuel-burn and gate-hold costs). Using data from Beijing Capital International (PEK) airport, four different departure pushback control policies, namely: (i) no-control (baseline case); (ii) traditional K-control; (iii) PDPC with a constant taxiway limit; and (iv) PDPC with varying taxiway limits; are compared. Detailed Monte Carlo simulations, which showcase the sensitivity of the total cost function to various problem parameters are presented, and the results indicate that deploying the PDPC policy results in a 42% reduction in total operational costs and a 68% reduction in fuel-burn (kg) as compared to the baseline case.  

To analytically reinforce these simulation results, an iterative Markov chain-based optimization algorithm is also developed to estimate the optimal values of the pushback rate and taxiway queue limit that minimize the total cost function. Such an analytical framework is very useful in the absence of reliable airport data as it only requires estimates of the historical pushback request rates and service times at the taxiway, while yet retaining the capability to closely mirror the simulation results. The Monte Carlo simulations as well as the Markov chain optimization model validate the strength and impact of the proposed PDPC policy and demonstrate its practical efficacy in reducing airport surface congestion when applied using data from PEK airport.