Minimizing passenger disruption and airline costs in hurricane recovery: A multimodal rescheduling approach

Air transportation is often affected by disruptions, both in the form of disasters that are caused by human error or natural phenomena. Such disruptions primarily affect passengers, in the form of travel delays and flight cancellations. Recovering airline schedules after disruptive events is particularly challenging for airlines due to unavailability of flights and/or their reduced capacity to address the demands of the affected passengers. In this work, we propose a multimodal rescheduling approach for airline passengers whose travel is disrupted by natural phenomena, such as hurricanes and tropical storms. The objective is to identify an optimal route, which may involve a combination of air and road travel, that minimizes system-level airline costs. The multimodal approach proposed here includes a multi-commodity network flow model where different origin–destination pairs for different travelers are treated as the different commodities. We incorporate transportation network risk in the form of a family of hop/risk side constraints. We test our approach on a simulated toy network and then proceed to use publicly available data to compare different airport network structures. The results from our computational study show that certain airline passengers may experience more inconvenience in comparison to others depending on the airport network topology of a specific airline.