Challenge:

Airlines need to identify the ideal times to fly to maximise demand, match capacity to demand and meet all operational requirements.  While at the same time establishing how to design their flight schedule in such a way as to maximise revenue.  With an almost infinite number of possible combinations, this process is inefficient and leads to higher costs and missed revenue opportunities.  In simple terms: every hour that a planes spends on the ground is wasted money. 

Solution:

Given data about point-to-point demand between every pair of cities over time, information about how much of the market an airline might be able to capture, and flight constraint and maintenance information, our algorithms are able to design an optimal, consistent flight schedule for the airline. 

This schedule takes into account constraints such as maintenance, ground times, penalties, tail assignment and connecting flights.  The schedule is optimal in the sense that it generates the maximum possible revenue for the airline. We have also developed tools for changing schedules on the fly (say in the event of a natural disaster or popular concert, when flying demand suddenly changes), and seamlessly stitching schedules together.  Our solution, unlike those of other industry players, is provably optimal.

By bringing together data from the multiple databases in different commercial areas, and combining this with external market and competitive data, fraXses makes it possible to deliver faster and better strategic planning decisions.  No matter the size of the airline or the complexity of the markets, the most advanced optimisation solutions are delivered to make better flight scheduling decisions. 

Benefits:

fraXses utilises systems that optimise all aspects of airline planning simultaneously, from flight times to aircraft routings. It generates new schedules as well as modifies existing ones and will revolutionise how airlines run their operations, providing empirical evidence of revenue improvements. 

A good metric for the performance of the fraXses algorithm is the hours that the fleet spends in the air, minus the hours that the fleet spends on the ground.  When comparing our algorithm to two existing airline solutions, we obtained the following increase in this metric: