Dr. Ahmed Abdelghany of Embry-Riddle has developed a new system to calibrate computer models that predict travelers’ choices, while taking capacity-constrained demand into consideration.
His new methodology could help airlines accurately predict passenger demand, which drives scheduling, fleet assignment and revenue management decisions.
“In each iteration, the weekly global demand of about 80 million air travelers is simulated, in more than half-million city-pairs worldwide, over nearly 770,000 flights and millions of itineraries,” Abdelghany explained.
Abdelghany’s method is a simulation-based tool designed to calibrate passenger itinerary choice models. His algorithm simulates air travelers versus all available itineraries, running through many iterations. At each iteration, the algorithm learns to minimize any discrepancies between the results of the simulation and data describing previous demand.
Dr. Ahmed Abdelghany has proved that more than 95 percent of the time his algorithms simulations consistently predicted both airline market share and the percentage of seats filled by passengers.
“In complex airline networks, it might be misleading to measure the quality of itineraries in terms of the number of their historical bookings, while ignoring the possible capacity limitations of those itineraries,” Abdelghany emphasized.
His latest research has been accepted for presentation at the 59th annual symposium of The Airline Group of the International Federation of Operational Research Societies (AGIFORS) in Seattle, Wash., Sept. 30 to Oct. 4.
