Revenue management system and associated method for updating and limiting future sales of spaces of a travel-related service

1. A revenue management system for updating and limiting future sales of spaces of a travel-related service in which the spaces are capable of being classified in a plurality of classes each having a different pricing, the revenue management system comprising:

a database comprising historical sales of the spaces;

a computing device configured to query the database, the computing device further configured to execute instructions embodied in:

a first forecast module configured to provide a first demand distribution that represents the probability of demand for each scenario of a remaining capacity of the spaces based upon the historical sales of the spaces;

a first optimization module configured to calculate a first plurality of inventory controls for the spaces based upon the first demand distribution and that optimizes revenue;

a second forecast module configured to provide a second demand distribution that represents the probability of demand for each scenario of a remaining capacity of the spaces that is different from the first demand distribution;

a second optimization module configured to calculate a second plurality of inventory controls for the spaces based upon the second demand distribution and that optimizes revenue;

a confidence module configured to measure a confidence level in the first demand distribution and to determine whether the confidence level in the first demand distribution is below a predetermined value; and

a switch module configured to automatically select between the second forecast module and the second optimization module and the first forecast module and the first optimization module,

wherein the switch module is further configured to select the second forecast module and the second optimization module if the confidence level in the first demand distribution is below the predetermined value, to select the second forecast module and the second optimization module in the absence of historical sales, and to select the second forecast module and the second optimization module until a booking period ends if the system switches to the second forecast module and the second optimization module for a second time during the booking period.

2. The revenue management system of claim 1 , wherein the second plurality of inventory controls for the spaces calculated by the optimization module ensures a maximum level of revenue in the maximum number of cases.

3. The revenue management system of claim 1 , wherein the second demand distribution is a uniform distribution between a maximum demand value and a minimum demand value.

4. The revenue management system of claim 3 , wherein the maximum and minimum demand values are defined by a specified percentage around a mean of the first demand distribution.

5. The reservation management system of claim 1 wherein the first inventory controls comprise a first bid-price curve, and the second inventory controls comprise a second bid-price curve that differs from the first bid-price curve.

6. The revenue management system of claim 5 , wherein the second optimization module is further configured to calculate the bid-price for a space for each scenario of a remaining capacity of spaces by calculating a revenue for a space for a first scenario of remaining capacity and comparing the calculated revenue of the space for the first scenario of remaining capacity with a calculated revenue for a space for a second scenario of remaining capacity, wherein the second scenario of remaining capacity has one more unit of capacity than the first scenario of remaining capacity.

7. The reservation management system of claim 1 wherein the future sales of spaces are in a first market, and the second demand distribution for the spaces is based upon the arrival patterns from a second market different from the first market.

8. A method of updating and limiting future sales of spaces of a travel-related service in which the spaces are capable of being classified in a plurality of classes each having a different pricing, the method comprising:

calculating with a computing device a first plurality of inventory controls for the spaces based upon a first demand distribution that represents the probability of demand for each scenario of a remaining capacity of the spaces and that optimizes revenue, wherein the first demand distribution is based on historical sales of the spaces;

measuring a confidence level in the first demand distribution;

determining if the confidence level in the first demand distribution is below a predetermined value;

if the confidence level in the first demand distribution is below the predetermined value, automatically selecting a second forecast module configured to be executed by the computing platform to provide a second demand distribution that represents the probability of demand for each scenario of a remaining capacity of the spaces that is different from the first demand distribution;

determining whether historical sales are present or absent;

in the absence of historical sales, selecting the second forecast module and the second optimization module;

during each booking period, monitoring for a switch in the system to the second forecast module and second optimization module for a second time;

in response to the system switching to the second forecast module and second optimization module for the second time during the booking period, selecting the second forecast module and the second optimization module until the end of the booking period; and

calculating with the computing device a second plurality of inventory controls for the spaces based upon the second demand distribution and that optimizes revenue.

9. The revenue management system of claim 8 wherein the second demand distribution is a uniform distribution between a maximum demand value and a minimum demand value.

10. The method of claim 8 wherein the first inventory controls comprise a first bid-price curve, and the second inventory controls comprise a second bid-price curve that differs from the first bid-price curve.

11. The method of claim 8 wherein the future sales of spaces are in a first market, and the second demand distribution for the spaces is based upon the arrival patterns from a second market different from the first market.

12. A computer program product comprising:

a non-transitory computer readable medium; and

a computer program stored on the non-transitory computer readable medium, the computer program comprising instructions for carrying out a method of updating and limiting future sales of spaces of a travel-related service in which the spaces are capable of being classified in a plurality of classes each having a different pricing, the instructions comprising:

calculating a first plurality of inventory controls for the spaces based upon a first demand distribution that represents the probability of demand for each scenario of a remaining capacity of the spaces and that optimizes revenue, wherein the first demand distribution is based on historical sales of the spaces;

measuring a confidence level in the first demand distribution;

determining if the confidence level in the first demand distribution is below a predetermined value;

if the confidence level in the first demand distribution is below the predetermined value, automatically selecting a second forecast module configured to be executed by the computing platform to provide a second demand distribution that represents the probability of demand for each scenario of a remaining capacity of the spaces that is different from the first demand distribution;

determining whether historical sales are present or absent;

in the absence of historical sales, selecting the second forecast module and the second optimization module;

during each booking period, monitoring for a switch in the system to the second forecast module and second optimization module for a second time;

in response to the system switching to the second forecast module and second optimization module for the second time during the booking period, selecting the second forecast module and the second optimization module until the end of the booking period; and

calculating with the computing device a second plurality of inventory controls for the spaces based upon the second demand distribution and that optimizes revenue.

13. The revenue management system of claim 12 wherein the second demand distribution is a uniform distribution between a maximum demand value and a minimum demand value.

14. The computer program product of claim 12 wherein the first inventory controls comprise a first bid-price curve, and the second inventory controls comprise a second bid-price curve that differs from the first bid-price curve.

15. The computer program product of claim 12 wherein the future sales of spaces are in a first market, and the second demand distribution for the spaces is based upon the arrival patterns from a second market different from the first market.