Dynamic cost analysis and overbooking optimization methods and systems

Abstract

A computer based system for maximizing revenue by determining an optimal quantity of a product to be sold is disclosed. The system determines the optimal number of seats to be sold for a flight based upon the flight's capacity and forecasted costs associated with the flight. The forecasting is based upon probabilistic distribution models and takes into account passenger itinerary data, passenger and market historical data, whether a passenger has flown on a previous leg of an itinerary, and the ripple denied boarding effect of reaccommodating a denied passenger. The system evaluates the potential effect of double selling a unit of inventory (e.g., seats). Downstreanm inventory control, revenue management and reservations systems may use the optimization data to affect the operation of the airline.

1 . A system comprising:
 a network interface communicating with a memory;   the memory communicating with an overbooking optimization processor;   the processor, when executing a computer program, executes operations comprising:   obtaining, by the processor, a capacity (CAP) and a no-show forecast (NSF) for a flight;   determining, by the processor, an optimal booking authorization level (AU) that minimizes an overbooking cost, wherein the overbooking cost is based upon the CAP, the NSF, a spoiled seat (SS) cost and a denied boarding (DB) cost, wherein the DB cost is dynamically calculated based upon a plurality of forecasts for a re-accommodation cost for each of a plurality of denied passengers for the flight; and   updating, by the processor and on a database, an authorization parameter for the flight based upon the AU.   
     
     
         2 . The system of  claim 1 , wherein at least one of a reservation system and a revenue management system uses the authorization parameter to determine a number of additional seats to be sold for the flight and a respective price for each additional seat. 
     
     
         3 . The system of  claim 1 , the operations further comprising determining the DB cost for a plurality of booking authorization levels (AUs). 
     
     
         4 . The system of  claim 3 , wherein the determining the DB cost for the plurality of AUs comprises determining for each of the plurality of AUs a forecasted number of denied passengers for the flight. 
     
     
         5 . The system of  claim 4 , the operations further comprising analyzing a plurality of flights in an airline network to identify a plurality of alternate accommodation (AA) flights, wherein each AA flight in the plurality of AA flights covers at least a same directional market as the flight. 
     
     
         6 . The system of  claim 5 , wherein the determining the re-accommodation cost comprises analyzing booking information for the plurality of AA flights. 
     
     
         7 . The system of  claim 6 , the operations further comprising selecting for a first denied passenger a first AA flight from the plurality of AA flights, wherein the first denied passenger is one of the plurality of denied passengers. 
     
     
         8 . The system of  claim 7 , the operations further comprising, selecting for a second denied passenger and based upon the selecting the first AA flight for the first denied passenger, a second AA flight from the plurality of AA flights, wherein the second denied passenger is one of the plurality of denied passengers and the second AA flight is one of the plurality of AA flights. 
     
     
         9 . The system of  claim 8 , the operations further comprising, in response to the second AA flight being scheduled to depart on a different day than the flight, adding an accommodations cost to the DB cost associated with the second denied passenger. 
     
     
         10 . The system of  claim 9 , wherein the accommodations cost comprises at least one of a hotel cost, a meal cost and a transportation cost for the second denied passenger. 
     
     
         11 . The system of  claim 4 , wherein the determining the forecasted number of denied passengers for the flight comprises determining based upon at least two of the CAP, the AU and the NSF. 
     
     
         12 . The system of  claim 11 , wherein the determining the forecasted number of denied passengers for the flight determining based upon at least one of a binomial distribution, a poisson distribution and a normal approximation of a binomial distribution. 
     
     
         13 . A system, comprising:
 a network interface communicating with a memory;   the memory communicating with a overbooking optimization processor;   the processor, when executing a computer program, executes operations comprising:   calculating, by the processor, a flight authorization level (AU) that minimizes an overbooking cost associated with the flight, the flight having a coach seating capacity (CAP),   wherein the overbooking cost is based upon a spoiled seat (SS) cost and a denied boarding (DB) cost, and   wherein the DB cost is dynamically calculated based upon a plurality of forecasts determining a re-accommodation cost for each of a plurality of denied passengers for the flight.   
     
     
         14 . The system of  claim 13 , the operations further comprising:
 analyzing a plurality of flights in an airline network to identify a plurality of alternate accommodation (AA) flights, wherein each AA flight the plurality of AA flights covers at least a same directional market as the flight; and   determining the re-accommodation cost by analyzing booking information for the plurality of AA flights.   
     
     
         15 . The system of  claim 14 , the operations further comprising:
 selecting for a passenger i  an AA flight j  from the plurality of AA flights; and   assigning passenger i  to AA flight j , wherein j is a member of (1 . . . J) flights, wherein J=the total number of the plurality of AA flights, wherein i is a member of (1 . . . I) passengers, and wherein I=the total number of the plurality of denied passengers for the flight.   
     
     
         16 . The system of  claim 15 , the operations further comprising:
 selecting, for a passenger i+1  and based upon the assigning passenger i  to AA flight j , an AA flight j+1  from the plurality of AA flights; and   assigning passenger i+1  to AA flight j+1 .   
     
     
         17 . The system of  claim 16 , wherein AA flight j  and AA flight j+1  are the same flight. 
     
     
         18 . The system of  claim 13 , the operations further comprising determining the No-Show-Rate by:
 determining a booked passenger no-show forecast (NSF) for each booked passenger on the flight, wherein the booked passenger NSF is a based upon whether the respective booked passenger flew on a previous leg of a passenger itinerary;   accumulating each respective booked passenger NSF to determine a booked passenger NSF for the flight;   aggregating, by the processor, the booked passenger NSF for the flight and an unbooked passenger NSF to create a flight NSF; and   calculating No-Show-Rate=(1−flight NSF).   
     
     
         19 . A computer-based method for determining an authorization level (AU) for a flight, the method comprising:
 determining, by an overbooking computer, a capacity (CAP) and a no-show forecast (NSF) for a flight;   determining, by the computer, an optimal booking authorization level (AU) that minimizes an overbooking cost, wherein the overbooking cost is based upon the CAP, the NSF, a SS cost and a DB cost, wherein the DB cost is dynamically calculated based upon the a plurality of forecasts determining a re-accommodation cost for each of a plurality of denied passengers for the flight; and   updating, by the computer and on a database, an authorization parameter for the flight based upon the AU.