A model for incorporating robustness into flight planning

Abstract

In scheduled air transport, airline profitability is strongly impacted by an airline's ability to construct flight schedules. Airlines face operational challenges such as schedule disruptions and limited resources affecting the efficiency of the operations. These delays may have cascading impacts on the subsequent flights, as they affect the crew's schedule and possibly aircraft schedules as well. Consequently, negative effects of the initial delay propagate through the network until the slack between flights can absorb the delay. This paper makes functional and economic comparisons between robust planning and disruption management in the case of delay. Approaches based on the Dantzig–Wolfe decomposition are used to solve the problem. The proposed technique was implemented on an actual data set of one of the major Iranian airlines with more than 35 aeroplanes that fly between 50 airports. The computational results show the proposed methodology can solve the problem optimally and significantly reduce the delay of flights.