Recovering from demand disruptions on an air cargo network

In this work we introduce the Air Cargo Schedule Recovery Problem (ACSRP). In this problem, a carrier airline has to reschedule flights and requests to adapt to last-minute demand changes. We consider three different possible crew management policies that translate into three different way to evaluate the costs of deviating from the original schedule. We formulated the ACSRP as a mixed integer linear programming problem, and tested our implementation on 24 original schedules with up to 30 orders and 8 airports, and 4 different disruption scenarios for each one. Our results show that, against a benchmark recovery policy where only cargo is re-routed, recovery can yield savings of roughly 10%. •We introduce the Air Cargo Schedule Recovery Problem (AC-SRP).•We provide a mathematical formulation for the ACSRP as a MILP.•We propose three different ways to penalize the deviation from the original schedule.•We test our formulation and recovery policies on 96 scenarios.•We obtain savings around 10%, compared against a benchmark recovery policy.