System and method for incorporating origination and destination effects into a vehicle assignment process

• US 6,076,067 A
• Filed: 11/05/1997
• Issued: 06/13/2000
• Est. Priority Date: 11/05/1997
• Status: Expired due to Term

• Current Assignee: Sabre GLBL Inc. (Sabre Corp.)
• Original Assignee: Sabre Incorporated (Sabre Corp.)
• Inventors: Smith, Barry C., Jacobs, Timothy L., Johnson, Ellis
• Primary Examiner(s): Tkacs, Stephen R.
• Assistant Examiner(s): Morgan, George D.
• Application Number:
  US08/964,875
• Time in Patent Office: 951 Days
• Field of Search: 705/7, 705/8, 705/1, 705/35
• US Class Current: 705/7.22
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06312 Adjustment or analysis of established resource schedule, e.g. resource or task levelling, or dynamic rescheduling
• CPC Class Codes: G06Q 10/06316 Sequencing of tasks or work
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Abstract

A comprehensive system and methodology for incorporating origination and destination network effects into a transportation industry'"'"'s vehicle assignment process. The invention utilizes a decomposition strategy to combine a simplified version of network segment-FAM with the network flow aspects of origination and destination yield management. The invention'"'"'s decomposition of the problem allows for the nonlinear aspects of the targeted origination and destination market effects to be isolated in origination and destination yield management, and subsequently incorporated in the vehicle assignment model using linear approximations to the total revenue function. The system operates either in "standalone" mode, or communicably attached to remote and local databases attendant to equipment and scheduling.

Claims

1. A system for determining the allocation of resources in a transportation industry comprising:

a computer having access to a storage device, the storage device including a data base incorporating the identity, number and capacity of different vehicles available for transportation over a transportation industry'"'"'s service network including a plurality of predetermined routes;

the storage device further including instructions for allocating a vehicle to one or more predetermined routes based upon combined origination and destination and individual route effects of the vehicle assignment, the instruction using a series of linear approximations;

a computer output device communicably attached to said system; and

a computer input device communicably attached to said system.

2. The system in accordance with claim 1 where the computer output capability is a computer printer.

3. The system in accordance with claim 1 where the computer output capability is a computer monitor.

4. The system in accordance with claim 1 where the computer input device is a computer keyboard.

5. The system in accordance with claim 1 where the computer input device is a computer mouse.

6. The system in accordance with claim 1 where the computer, computer storage device, computer output capability and computer input capability are communicably linked via a local area network.

7. A method for vehicle assignment incorporating origination and destination effects comprising the steps, performed by a processor, of:

(1) initializing a fleet vehicle assignment model based upon assumed vehicle capacities;

(2) generating fleet vehicle assignments and origination and destination fleet assignment model profit predictions from step 1;

(3) generating origination and destination yield management network profit prediction and bid prices based upon fleet vehicle assignments;

(4) comparing results of generated origination and destination fleet assignment model profit prediction to previously generated or produced origination and destination network profit prediction; and

(5) generating a revenue approximation if previously generated or produced origination and destination fleet assignment model profit prediction and previously generated or produced origination and destination network profit prediction results are outside of a predetermined range.

8. The method in accordance with claim 7 further comprising the step of determining if two previous origin and destination fleet vehicle assignment model solutions have been found after generating a revised bid price approximation.

9. The method in accordance with claim 7 wherein fleet vehicle assignments and origination and destination fleet assignment model predictions are generated based upon determining previous origin and destination fleet assignment model solutions.

10. The method in accordance with claim 9 wherein fleet vehicle assignment and origination and destination profit prediction is generated based upon having determined two origin and destination fleet vehicle assignment model solutions.

11. The method of claim 7 wherein the fleet assignment model comprises an aircraft assignment model.

12. The method of claim 7 further comprising the step of initializing a fleet vehicle assignment model with bid prices based upon assumed vehicle capacities.

13. The method of claim 7 further comprising the step of initializing generating fleet vehicle assignments and origination and destination fleet assignment model profit predictions based upon bid prices.

14. The method of claim 7 further comprising the step of assigning vehicles to network routes based upon the estimated expected network profit.

15. The method of claim 7 wherein the method is implemented on a computer.

16. The method of claim 7 wherein the method is implemented on a computer, computer storage device, computer output device and computer input device communicably linked via a local area network.

17. A method for vehicle assignment incorporating origination and destination effects comprising the steps, performed by a processor, of:

(1) initializing a fleet vehicle assignment model based upon assumed vehicle capacities;

(2) generating fleet vehicle assignments and origination and destination fleet assignment model profit predictions from step 1;

(3) generating origination and destination yield management network profit prediction and bid prices based upon fleet vehicle assignments;

(4) comparing results of generated origination and destination fleet assignment model profit prediction to previously generated or produced origination and destination network profit prediction;

(5) generating a revenue approximation if previously generated or produced origination and destination fleet assignment model profit prediction and previously generated or produced origination and destination network profit prediction results are outside of a predetermined range; and

determining an appropriate integer assignment if the fleet assignment model profit prediction and previously generated origination and destination network profit prediction results are within a predetermined range.

18. The method of claim 17 further comprising the step of generating an estimated expected network profit having once determined an appropriate integer assignment.