Carrier path prediction based on dynamic input data
A method and system for managing carrier vessel information are provided. A carrier path and shipment planning system receives carrier information associated with individual carrier vessels from a plurality of carrier information sources. Based on the carrier information the carrier path and shipment planning system processes the carrier information to form complete path scenarios. The carrier path and shipment planning system associates control rules to the complete path scenarios to determine one or more candidate paths. The carrier path and shipment planning system can then generate various interfaces for identifying selected, ranked paths, information associated with a competitive marketplace and availability information for contracting for cargo shipment. A user can then further manipulate the user interfaces for scenario planning or filtering available selections.
1. A computer-implemented method comprising:
obtaining a set of carrier information for individual identifiable vessels;
forming a plurality of skeleton scenario paths for the individual identifiable vessels from the set of carrier information, wherein each skeleton scenario path of the plurality of skeleton scenario paths for the individual identifiable vessels is defined by one or more anchor points;
selecting a first portion of a plurality of target paths corresponding to a first portion of the skeleton paths;
assigning attributes to the first portion of the plurality of target paths, wherein an attribute associated with individual target paths is based on a determined probability that the individual target path is a correct travel path for the identifiable vessel; and
generating a ranked list of the plurality of target paths for the individual identifiable vessels based on application of a scoring function, wherein the scoring function is at least in part based on the attributes.
2. The computer-implemented method as claim 1 further comprising automatically combining a second portion of the plurality of skeleton scenario paths to form a second portion of the plurality of target paths for the individual identifiable vessels, wherein the second portion of the plurality of skeleton scenario paths are combined according to common anchor points.
3. The computer-implemented method as recited in claim 2 , further comprising assigning attributes to the second portion of the plurality of target paths.
4. The computer-implemented method as recited in claim 1 wherein the determined probability that the individual target path is a correct travel path for the identifiable vessel includes historical voyage information.
5. The computer-implemented method as recited in claim 1 further comprising for defined locations, generating a value indicator associated with a density of at least subset of individual identifiable vessels.
6. The computer-implemented method as recited in claim 1 wherein the first portion of the plurality of skeleton paths include skeleton paths in the plurality of skeleton paths that are not combinable by anchor points.
7. The computer-implemented method as recited in claim 1 further comprising adjusting the ranked list based on additional inputs.
8. The computer-implemented method as recited in claim 1 , wherein application of the scoring function includes scoring the plurality of target paths according to control rules recalled from a control rules memory and defining a scoring function to be applied to the target path, wherein the control rules are applied to the plurality of target paths.
9. The computer-implemented method of claim 8 , wherein the control rules applied by a carrier path and shipment planning service associate a score to a target path based on a determined degree of suitability for the target path.
10. The computer-implemented method of claim 8 , wherein the control rules applied by a carrier path and shipment planning service associate a score to a target path based on a determined degree of feasibility for the target path.
11. The computer-implemented method as recited in claim 1 further comprising receiving the set of carrier information from a plurality of carrier information sources.
12. The computer-implemented method as recited in claim 1 , wherein the set of carrier information is received in accordance with specific application programming information, wherein individual application programming information corresponds to a different format of carrier information.
13. The computer-implemented method of claim 1 , wherein generating a ranked list of the plurality of target paths for the individual identifiable vessels based on application of a scoring function includes applying a penalty model to the plurality of target paths, the penalty model reflective of location information included in the plurality of target paths.
14. The computer-implemented method as recited in claim 1 wherein generating a ranked list of the plurality of target paths for the individual identifiable vessels is further based on application of a penalty model.
15. The computer-implemented method as recited in claim 14 wherein application of a penalty model comprises applying a penalty for repairs, stops, loading, or discharging.
16. The computer-implemented method as recited in claim 1 further comprising generating a graph representative of the first portion of the plurality of target paths.
17. The computer-implemented method as recited in claim 16 wherein the graph is based on the probability that the individual target path is correct.
18. A computer-implemented method comprising:
forming a plurality of skeleton scenario paths for individual identifiable vessels from a set of carrier information, wherein each skeleton scenario path of the plurality of skeleton scenario paths for the individual identifiable vessels is defined by one or more anchor points;
identifying a first subset of a plurality of target paths corresponding to a portion of the plurality of skeleton paths;
assigning individual attributes to individual target paths in the first subset of the plurality of target paths, wherein a attribute associated with each individual target path is based on a characterization of probability of the first individual target paths accurately encompasses a path of travel for the identifiable vessel; and
automatically combining a second subset of the plurality of skeleton scenario paths to form a second portion of the plurality of target paths for the individual identifiable vessels, wherein the second subset of the plurality of skeleton scenario paths are combined according to common anchor points; and
scoring the plurality of target paths according to control rules recalled from a control rules memory and defining a scoring function to be applied to the target path, wherein the control rules are applied to the plurality of target paths and are at least in part based on attributes.
19. The computer-implemented method as recited in claim 18 , wherein the probabilities are at least in part based on historical voyage information.
20. The computer-implemented method as recited in claim 18 further comprising generating an interface responsive to a request, the interface including density information of at least subset of individual identifiable vessels.
21. The computer-implemented method as recited in claim 18 wherein the first subset of the plurality of skeleton paths are not combinable by anchor points.
22. The computer-implemented method as recited in claim 18 , wherein scoring the plurality of target paths includes scoring the plurality of target paths continuously during a voyage.
23. A computer-implemented method comprising:
forming a plurality of skeleton scenario paths for individual identifiable vessels from information associated with activities attributable to the individual identifiable vessels and wherein each skeleton scenario path of the plurality of skeleton scenario paths for the individual identifiable vessels is defined by one or more anchor points;
for a first subset of a plurality of target paths, associating a probability that individual target paths of the first subset of the plurality of target paths is correct;
assigning attributes to the first subset of the plurality of target paths, wherein a attribute associated with individual target paths is based on the associated probability that the individual target paths of the first subset of the plurality of target paths is correct; and
scoring the plurality of target paths according to control rules recalled from a control rules memory and defining a scoring function to be applied to the plurality of target paths, wherein the control rules are applied to the plurality of target paths to generate a ranked list of target paths and are at least in part based on the attributes.
24. The computer-implemented method of claim 23 , wherein the information associated with activities attributable to the individual identifiable vessels is based on a plurality of carrier information sources.
25. The computer-implemented method as recited in claim 23 , wherein the probabilities are based on historical voyage information.