SYSTEM AND METHOD TO OPTIMIZE MASS TRANSPORT VEHICLE ROUTING BASED ON TON-MILE COST INFORMATION

• US 20130138330A1
• Filed: 11/25/2011
• Published: 05/30/2013
• Est. Priority Date: 11/25/2011
• Status: Abandoned Application

• Current Assignee: Wipro Limited
• Original Assignee: Jiefeng Xu
• Inventors: XU, JIEFENG, Kapoor, Ajesh, Maheshwari, Amit
• Application Number:
  US13/304,420
• Publication Number:
  US 20130138330A1
• Time in Patent Office: Days
• US Class Current: 701/117
• CPC Class Codes: G06Q 10/047 Optimisation of routes or paths, e.g. travelling salesman problem
• CPC Class Codes: G06Q 10/08 Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
• CPC Class Codes: G06Q 10/0834 Choice of carriers

Abstract

A system and method to optimize mass transport vehicle routing based on additional ton-mile cost information are disclosed. In one embodiment, a starting location and a plurality of customer locations associated with a warehouse and a plurality of customers, respectively, are identified. Furthermore, a plurality of pairs of locations is identified using the starting location and plurality of customer locations. Mileage cost information and ton-mile cost information are then dynamically computed for each of the plurality of pairs of locations. In addition, sets of mass transport vehicle routes between the starting location and plurality of customer locations are dynamically determined using the pairs of locations and a number of vehicles to be used. Moreover, trip cost information is computed, in real-time, for each set of mass transport vehicle routes. Also, an optimized set of mass transport vehicle routes is determined, in real-time, using the trip cost information.

Claims

1. A computer implemented method for optimizing mass transport vehicle routing based on additional ton-mile cost information, comprising:

identifying a starting location and a plurality of customer locations associated with a warehouse and a plurality of customers, respectively, by a mass transport vehicle routing engine running on the computer;

identifying a plurality of pairs of locations using the starting location and the plurality of customer locations by the mass transport vehicle routing engine running on the computer;

dynamically computing mileage cost information and ton-mile cost information for each of the plurality of pairs of locations by the mass transport vehicle routing engine running on the computer;

dynamically determining, by the mass transport vehicle routing engine running on the computer, sets of mass transport vehicle routes between the starting location and the plurality of customer locations using the plurality of pairs of locations and a number of vehicles to be used;

real-time computing trip cost information for each set of mass transport vehicle routes using the mileage cost information and ton-mile cost information by the mass transport vehicle routing engine running on the computer; and

real-time determining an optimized set of mass transport vehicle routes from the sets of mass transport vehicle routes using the computed trip cost information by the mass transport vehicle routing engine running on the computer.

2. The computer implemented method of claim 1, further comprising:

receiving real-time disruption information associated with the optimized set of mass transport vehicle routes by the mass transport vehicle routing engine running on the computer; and

obtaining a further optimized set of mass transport vehicle routes using the real-time disruption information by the mass transport vehicle routing engine running on the computer.

3. The computer implemented method of claim 2, wherein the starting location and the plurality of customer locations associated with the warehouse and the plurality of customers, respectively, are identified, in real-time, by a mass transport vehicle routing engine running on the computer, based on the real-time disruption information.

4. The computer implemented method of claim 3, wherein the plurality of pairs of locations are identified, in real-time, using the starting location and the plurality of customer locations, by a mass transport vehicle routing engine running on the computer, based on the real-time disruption information.

5. The computer implemented method of claim 4, wherein the real-time disruption information comprises real-time order information, traffic information, accident information, fuel cost, conditions associated with the plurality of customer locations and vehicle conditions.

6. The computer implemented method of claim 1, further comprising:

receiving order information, fleet information and company work rules and regulations by the mass transport vehicle routing engine running on the computer, wherein the order information comprises information selected from the group consisting of a time limit, a customer order and a customer address and wherein the fleet information comprises information selected from the group consisting of a number of available vehicles and vehicle characteristics.

7. The computer implemented method of claim 4, wherein the vehicle characteristics comprise characteristics selected from the group consisting of a vehicle energy type based on energy consumption, a vehicle class, a vehicle size, a vehicle weight, a vehicle capacity, a vehicle energy function, and a vehicle maintenance history.

8. The computer implemented method of claim 4, wherein the plurality of customer locations associated with the plurality of customers is identified by from the received order information.

9. The computer implemented method of claim 1, wherein each set of mass transport vehicle routes comprises one or more mass transport vehicle routes determined based on the number of vehicles used.

10. The computed implemented method of claim 1, wherein the number of vehicles to be used is dynamically computed by the mass transport vehicle routing engine using a number of available vehicles.

11. The computed implemented method of claim 1, wherein the number of vehicles to be used is provided by a user.

12. The computed implemented method of claim 1, wherein each set of mass transport vehicle routes comprises one or more mass transport vehicle routes that cover the plurality of customer locations using the number of vehicles.

13. The computed implemented method of claim 1, wherein the ton-mile cost information is cost information associated with distance travelled by a vehicle and net weight of load carried by the vehicle over the distance.

14. The computer implemented method of claim 1, wherein the trip cost information is computed using an equation:

trip cost information=mileage cost information+k*(ton-mile cost information) where k is a weight constant.

15. The computer implemented method of claim 1, wherein real-time determining the optimized set of mass transport vehicle routes using the computed trip cost information by the mass transport vehicle routing engine running on the computer comprises:

selecting a first set of mass transport vehicle routes and a second set of mass transport vehicle routes from the determined sets of mass transport vehicle routes by the mass transport vehicle routing engine running on the computer;

obtaining the trip cost information associated with the first set of mass transport vehicle routes and the second set of mass transport vehicle routes by the mass transport vehicle routing engine running on the computer;

comparing the trip cost information associated with the first set of mass transport vehicle routes with the trip cost information associated with the second set of mass transport vehicle routes by the mass transport vehicle routing engine running on the computer; and

declaring one of the first set of mass transport vehicle routes and second set of mass transport vehicle routes associated with minimum of the trip cost information as an optimized set of mass transport vehicle routes based on the comparison by the mass transport vehicle routing engine running on the computer.

16. The computer implemented method of claim 15, further comprising:

repeating the steps of selecting, obtaining, comparing and declaring for a next set of mass transport vehicle routes in the sets of mass transport vehicle routes and the optimized set of mass transport vehicle routes by the mass transport vehicle routing engine running on the computer.

17. A transport management system (TMS) for optimizing mass transport vehicle routing based on additional ton-mile cost information, comprising:

a processor;

memory coupled to the processor; and

a mass transport vehicle routing engine residing in the memory, wherein the mass transport vehicle routing engine comprises;

a location identification module to identify a starting location and a plurality of customer locations associated with a warehouse and a plurality of customers, respectively;

a location pair identification module to identify a plurality of pairs of locations using the starting location and the plurality of customer locations;

a mileage cost matrix module to dynamically compute mileage cost information for each of the plurality of pairs of locations;

a ton-mile cost matrix module to dynamically compute ton-mile cost information for each of the plurality of pairs of locations; and

a mass transport vehicle routes planning engine to dynamically determine sets of mass transport vehicle routes between the starting location and the plurality of customer locations using the plurality of pairs of locations and a number of vehicles to be used, compute, in real-time, trip cost information for each set of mass transport vehicle routes using the mileage cost information and ton-mile cost information and determine, in real-time, an optimized set of mass transport vehicle routes from the sets of mass transport vehicle routes using the computed trip cost information.

18. The TMS of claim 17, further comprising:

a real-time disruption information module to store real-time disruption information associated with the optimized set of mass transport vehicle routes; and

a real-time mass transport vehicle routing engine to obtain a further optimized set of mass transport vehicle routes using the real-time disruption information.

19. The TMS of claim 18, wherein the location identification module is configured to identify, in real-time, the starting location and a plurality of customer locations associated with the warehouse and the plurality of customers, respectively, based on the real-time disruption information.

20. The TMS of claim 19, wherein the location pair identification module is configured to identify, in real-time, the plurality of pairs of locations using the starting location and the plurality of customer locations based on the real-time disruption information.

21. The TMS of claim 20, wherein the real-time disruption information comprises real-time order information, traffic information, accident information, fuel cost, vehicle conditions and conditions associated with the plurality of customer locations.

22. The TMS of claim 17, further comprising:

an order information module, a fleet information module and a company work rules and regulations module to store order information, fleet information and company work rules and regulations, respectively, wherein the order information comprises information selected from the group consisting of a time limit, a customer order and a customer address and wherein the fleet information comprises information selected from the group consisting of a number of available vehicles and vehicle characteristics.

23. The TMS of claim 22, wherein the plurality of customer locations associated with the plurality of customers is identified from the received order information.

24. The TMS of claim 22, wherein the mass transport vehicle routes planning engine receives the order information, fleet information and company work rules and regulations from the order information module, fleet information module and company work rules and regulations module.

25. The TMS of claim 22, wherein the vehicle characteristics comprise characteristics selected from the group consisting of a vehicle energy type based on energy consumption, a vehicle class, a vehicle size, a vehicle weight, a vehicle capacity, a vehicle energy function, and a vehicle maintenance history.

26. The TMS of claim 17, wherein each set of mass transport vehicle routes comprises one or more mass transport vehicle routes determined based on the number of vehicles to be used.

27. The TMS of claim 26, wherein the number of vehicles to be used is dynamically computed by the mass transport vehicle routing engine using a number of available vehicles.

28. The TMS of claim 26, wherein the number of vehicles to be used is provided by a user.

29. The TMS of claim 17, wherein each set of mass transport vehicle routes comprises one or more mass transport vehicle routes that cover the plurality of customer locations using the number of vehicles.

30. The TMS of claim 17, wherein the ton-mile cost information is cost information associated with distance travelled by a vehicle and net weight of load carried by the vehicle over the distance.

31. The TMS of claim 17, wherein the trip cost information is computed using an equation:

trip cost information=mileage cost information+k*(ton-mile cost information) where k is a weight constant.

32. The TMS of claim 17, wherein the mass transport vehicle routes planning engine is configured to:

select a first set of mass transport vehicle routes and a second set of mass transport vehicle routes from the sets of mass transport vehicle routes;

obtain the trip cost information associated with the first set of mass transport vehicle routes and the second set of mass transport vehicle routes;

compare the trip cost information associated with the first set of mass transport vehicle routes with the trip cost information associated with the second set of mass transport vehicle routes; and

declare one of the first set of mass transport vehicle routes and second set of mass transport vehicle routes associated with minimum of the trip cost information as an optimized set of mass transport vehicle routes based on the comparison.

33. The TMS of claim 32, the mass transport vehicle routes planning engine is further configured to:

repeat the steps of selecting, obtaining, comparing and declaring for a next set of mass transport vehicle routes in the sets of mass transport vehicle routes and the optimized set of mass transport vehicle routes.

34. At least one non-transitory computer-readable storage medium to optimize mass transport vehicle routing based on additional ton-mile cost information having instructions that, when executed by a computing device, cause the computing device to:

identify a starting location and a plurality of customer locations associated with a warehouse and a plurality of customers, respectively;

identify a plurality of pairs of locations using the starting location and plurality of customer locations;

dynamically compute mileage cost information and ton-mile cost information for each of the plurality of pairs of locations;

dynamically determine sets of mass transport vehicle routes between the starting location and the plurality of customer locations using the plurality of pairs of locations and a number of vehicles to be used;

compute, in real-time, trip cost information for each set of mass transport vehicle routes using the mileage cost information and ton-mile cost information; and

determine, in real-time, an optimized set of mass transport vehicle routes from the sets of mass transport vehicle routes using the computed trip cost information.

35. The at least one non-transitory computer-readable storage medium of claim 34, further comprising:

receiving real-time disruption information associated with the optimized set of mass transport vehicle routes; and

obtaining a further optimized set of mass transport vehicle routes using the real-time disruption information.

36. The at least one non-transitory computer-readable storage medium of claim 34, further comprising:

receiving order information, fleet information and company work rules and regulations, wherein the order information comprises information selected from the group consisting of a time limit, a customer order and a customer address and wherein the fleet information comprises a number of available vehicles and vehicle characteristics.