Feeding the bottleneck: airport congestion during relief operations

Abstract

Purpose Scheduling the airlift of relief supplies into a damaged or small airport during a crisis is complex yet crucial. The volume of cargo and flights can temporarily overwhelm the airport’s capacity and the mix of flights adds complexity. The purpose of this paper is to better characterize airport operations during a crisis, to develop a model that can assess strategies for scheduling flights and to draw implications for decision makers. Design/methodology/approach First, empirical data are analyzed to characterize airport operations. Previously unreported data from the 2010 Haiti earthquake response in the form of a “flight log” are analyzed to provide new insights and parameters. Alternate scheduling strategies are drawn from review of the literature and After Action Reports. Second, a queuing model is developed to understand operations in past crises and predict the impact of alternate scheduling strategies. Empirical data provide the parameters for airport scenarios evaluated. Findings Unloading capacity is seen to be the bottleneck but also to not be fully utilized, suggesting that a more aggressive flight schedule is needed. Scheduling flights is shown to be a tradeoff between volume of aid delivered and flights that must be diverted. The proper mix of aircraft and prioritized divert policies also provide benefits. Finally, it is beneficial, though perhaps counterintuitive, to create a parking buffer upstream from the unloading bottleneck. Originality/value Analysis of previously unreported data from the Haiti earthquake provides new insights regarding airport parking and unloading operations. A new model of airport scheduling for disaster response is proposed. The model differs from other humanitarian airlift models in that it focuses on aircraft parking and unloading. It differs from commercial aircraft scheduling and gate assignment in the objective used.

Critical Airport Infrastructure Disaster Resilience: A Framework and Simulation Model for Rapid Adaptation

“…In the case of airports, key processes such as scheduling, parking and loading/unloading are impacted by a disaster and hence have an important effect on the airport operations (Veatch and Goentzel 2018). As such, what is needed is a systematic consideration of rapid adapt-7…”

“…KPI 1: Cargo Processed (tons/hour): The cargo processed at the airport measures the number of tons of cargo that leaves the airport system (or system components) per hour, which is an indicator for the processing capacity of the airport. The inflow of cargo is beyond the control of the decision-makers at the airport (Veatch and Goentzel 2018). As such, it presents one of the external factors that the airport system rapidly needs to adapt to.…”

“…We illustrate and test our framework via a stylized case study that functions as a proof of concept. The model and underlying data are based on a combination of empirical data from the Nepal earthquake of 2015 (Aydin et al 2018;Baharmand et al 2017) and the Haiti earthquake of 2010 (Veatch and Goentzel 2018). The data sets of these two disasters were gathered via expert interviews with professionals in airports in disasters (from US Airforce, DHL and Dnata) and literature research.…”

“…Prioritization mechanism on aircraft size. Wide-body aircrafts need less time on the ground per cargo unit compared to smaller aircrafts (Veatch and Goentzel 2018).…”

“…This new role comes with an increase of incoming aircrafts bringing supplies or aid workers. For an airport already struggling to regain its normal capacity, this additional load often creates congestion with significant bottlenecks at the airport hampering the ensuing response (Holguín-Veras et al 2012;Veatch and Goentzel 2018).…”