An Integrated Fuzzy Multi Criteria Approach for Robust Pairing Selection in Aviation Scheduling

Risk is present in almost every economic activity these days. The same uncertainty affects the aviation industry and requires disruption management from the airlines. With the relentless push for efficiency, aviation networks today are getting more and more optimized and hence inflexible. Even a small disturbance in such a tight network has a ripple effect which travels for long distances and hence effects a large portion of the network. Adding to the difficulty is the fact that handling disruptions has a lot of subjectivity and uncertainty involved. Most of the times there is a very little information available and also the action time window is very narrow. This makes processing the situation even more difficult. This warrants to have a proactive disruption management strategy by making the airline network more robust and hence more flexible to suitably absorb small shocks. This study is an effort towards this end by quantifying the robustness of each flight pairing and then choosing the best pairings on both the criteria of robustness and cost rather than on cost alone. An integrated fuzzy multi criteria method based on popular approach called technique for order preference by similarity to the ideal solution (TOPSIS) is used here for this purpose. A numerical example is solved to explain the workings of the methodology.