US 11,972,373 B2
Time-based decomposition for supply chain optimization problem
Devanand R, Bangalore (IN); Narayan Nandeda, Ujjain (IN); and Tushar Shekhar, Bangalore (IN)
Assigned to Blue Yonder Group, Inc., Scottsdale, AZ (US)
Filed by Blue Yonder Group, Inc., Scottsdale, AZ (US)
Filed on Aug. 9, 2023, as Appl. No. 18/232,162.
Application 18/232,162 is a continuation of application No. 18/105,717, filed on Feb. 3, 2023, granted, now 11,755,967.
Application 18/105,717 is a continuation of application No. 17/739,861, filed on May 9, 2022, granted, now 11,586,995, issued on Feb. 21, 2023.
Application 17/739,861 is a continuation of application No. 16/722,866, filed on Dec. 20, 2019, granted, now 11,328,229, issued on May 10, 2022.
Claims priority of provisional application 62/895,870, filed on Sep. 4, 2019.
Claims priority of provisional application 62/856,283, filed on Jun. 3, 2019.
Prior Publication US 2023/0385720 A1, Nov. 30, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 10/04 (2023.01); G06Q 10/0631 (2023.01)
CPC G06Q 10/04 (2013.01) [G06Q 10/06315 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for iteratively solving a supply chain demand planning problem modeled as a linear programming (LP) problem, comprising:
a computer, comprising a processor and memory, the computer configured to:
receive a multi-period matrix formulation of at least a portion of an LP supply chain demand planning problem;
map constraints of the LP supply chain demand planning problem and variables of the LP supply chain demand planning problem to a planning horizon;
formulate at least two time-based decomposed subproblems by decomposing the LP supply chain demand planning problem at one or more decomposition boundaries;
identify complicating constraints;
perform masterless iteration with subgradient descent; and
repeat the formulate, identify and perform to incrementally improve an overall solution until a stopping criteria is met.