Linear Regression Modeling For Load Factors

A system, comprising:

• a network interface communicating with a memory;
• the memory communicating with a processor;
• the processor, when executing a computer program, executes operations comprising:
• determining, by an optimizer module in communication with the processor, a capacity (CAP) from an airline central data repository;
• forecasting, by the processor and in real-time iteratively throughout a period of time, a no-show forecast (NSF) based on passenger name record characteristics from a passenger system;
• determining, by the optimizer module in communication with the processor and using a flight cost prediction model in a forecaster module and in real-time iteratively throughout the period of time, an optimal booking authorization level (AU) that minimizes an overbooking cost,
• determining, by a cost engine in communication with the processor and in real-time iteratively throughout the period of time, a spoiled seat (SS) cost;
• determining, by the cost engine in communication with the processor and in real-time iteratively throughout the period of time, a denied boarding (DB) cost based on a probability of a volunteer not taking the flight;
• wherein the overbooking cost is based upon the CAP, the NSF, the SScost and the DB cost,
• wherein the DB cost is based on actual passengers booked, market load factors, accommodations cost and a probability a denied boarding will result in a voucher, and
• 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;
• wherein the DB cost is determined by:
• DB costi=DDBi*[(1−ncf)*(voucher_amt*b*pvi+(ill_will+exp_invol_costi)*(1−pvi)+HMTi)];
• where,
• DB costi is DB cost of the ith passenger who is denied boarding;
• ncf is no Compensation Factor, the percentage of DBs that do not qualify to be compensated due to non-compliance, 0≦ncf≦1;
• voucher_amt is the actual amount of the voucher offered to passengers who volunteer to DB;
• b is a breakage factor, the expected percentage of voucher dollars that will be used, 0≦b≦1;
• given i DBs, pvi is the expected percentage of volunteers, calculated from a linear regression model using historical data, 0≦pv≦1;
• ill_will is the extra cost added due to bad customer image and possible loss of customers due to involuntarily denying boarding to passengers;
• exp_invol_costi is the expected payout to an involuntary DB passenger;
• HMTi is the expected hotel, meal and transportations costs of the ith DB passenger, based on the time to accommodate the passenger;
• and,
• DDBi is a double DB factor, increases the DB cost based on the probability that this DB causes another DB, wherein DDBi increases depending on the load factor of an entire directional market and the station load factor for that day, and wherein DDBi>1.
• modeling, by the cost engine in communication with the processor and in real-time iteratively throughout the period of time, DB cost as an aggregate, for each passenger denied boarding, of a breakage adjusted voucher cost, an involuntary rate draft cost, a rolling denied boarding marginal cost and a secondary accommodations cost;
• updating, by the processor and on a database and in real-time iteratively throughout the period of time, an authorization parameter to create an updated authorization parameter for the flight based upon the AU to maximize revenue for the flight and minimize the costs of overbooking;
• providing, by the processor and to a revenue management system and in real-time iteratively throughout the period of time, the updated authorization parameter,
• wherein the updated authorization parameter impacts the revenue management system and a reservation system,
• wherein the revenue management system determines, based on the updated authorization parameter, a number of additional seats to be sold for the flight and a respective price for each additional seat,
• wherein the revenue management system transmits to the reservation system the number of additional seats to be sold for the flight and the respective price for each additional seat.
• creating, by the processor and in real-time, a voucher for the number of additional seats for the flight, wherein the voucher changes throughout the day based on the updating the updated authorization parameter and most current conditions to minimize costs;
• and
• providing, by the processor and in real-time and to a customer mobile device, the voucher for the number of additional seats for the flight.

A computer-based method for determining an authorization level (AU) for a flight, the method 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.