A proactive crew recovery decision support tool for commercial airlines during irregular operations

In this paper, a decision support tool that automates crew recovery during irregular operations for large-scale commercial airlines is presented. The tool is designed for airlines that adopt the hub–spoke network structure. The advance of this tool over the existing ones is that it recovers projected crew problems that arise due to current system disruptions. In other words, it proactively recovers crew problems ahead of time before their occurrence. In addition, it gives a wide flexibility to react to different operation scenarios. Also, it solves for the most efficient crew recovery plan with the least deviation from the originally planned schedule. The tool adopts a rolling approach in which a sequence of optimization assignment problems is solved such that it recovers flights in chronological order of their departure times. In each assignment problem, the objective is to recover as many flights as possible while minimizing total system cost resulting from resource reassignments and flight delays. The output of this tool is in the form of new crew trip pairs that cover flights in the considered horizon. A test case is presented to illustrate the model capabilities to solve a real-life problem for one of the major commercial airlines in the US.