US 12,438,916 B2
Intelligent automated planning system for large-scale operations
Jason Crabtree, Vienna, VA (US); and Andrew Sellers, Monument, CO (US)
Assigned to QOMPLX LLC, Reston, VA (US)
Filed by QOMPLX LLC, Reston, VA (US)
Filed on Feb. 5, 2024, as Appl. No. 18/433,378.
Application 18/433,378 is a continuation of application No. 17/106,997, filed on Nov. 30, 2020, granted, now 11,979,433.
Application 17/106,997 is a continuation in part of application No. 15/931,534, filed on May 13, 2020, abandoned.
Prior Publication US 2024/0179185 A1, May 30, 2024
Int. Cl. G06F 16/2458 (2019.01); G06F 16/951 (2019.01); H04L 9/40 (2022.01)
CPC H04L 63/20 (2013.01) [G06F 16/2477 (2019.01); G06F 16/951 (2019.01); H04L 63/1425 (2013.01); H04L 63/1441 (2013.01)] 36 Claims
OG exemplary drawing
 
1. A computing system for prediction of future performance of large-scale operations and to manage financial, operational and market execution risk employing an intelligent automated planning system, the computing system comprising:
one or more hardware processors configured for:
instantiating a distributed computational graph comprising nodes representing data transformations and edges representing messages between the nodes, wherein:
the distributed computational graph comprises a data processing workflow for analyzing a large-scale operational plan and associated risk factors based on market, operations and financial data retrieved over the web from both corporate operations data stores and other exogenous sources; and
the data transformation of one or more of the nodes comprises receipt of data from at least one physical or virtual sensor or application telemetry source;
storing the data processing workflow of the distributed computational graph;
performing a plurality of analytic and simulation computations as directed by the data processing workflow of the distributed computational graph;
producing a first result comprising a first plurality of estimated future states of the large-scale operational plan under at least one scenario over a finite time horizon; and
producing a second result comprising at least one additional scenario and a second plurality of estimated future states associated with the at least one additional scenario, and a plurality of associated risk factors and their impact on the first and second pluralities of estimated future states.