A matheuristic approach to the air-cargo recovery problem under demand disruption

Air cargo transport is subject to unpredictable changes in expected demand, necessitating adjustments to itinerary planning to recover from such disruptions. We study a flight rescheduling problem to react to cargo demand disruptions in the short run. To increase flexibility, we consider two different cargo assignment policies. We propose a matheuristic approach to solve the problem that provides high-quality solutions in a short computational time, based on column generation in which each subproblem is solved using an ad-hoc heuristic. The approach is tested on demand disruption instances containing up to 75 air cargo orders with different penalty levels. The results show that the proposed method improves profit by 54% over the solution generated by a commercial MIP solver within a 1-h time limit, and by 15% over the solution with the routes fixed as in the original flight planning that only allows cargo to be re-routed. We also show that there exist incremental benefits in the range of 3–5% by allowing cargo for a given order to be transported by various aircraft.