公开(公告)号：US12045851B2

公开(公告)日：2024-07-23

申请号：US17359908

申请日：2021-06-28

Applicant: Kinaxis Inc.

Inventor： Kanchana Padmanabhan ,  Anneya Golob ,  Brian Keng

IPC: G06Q30/0242 ,  G06F40/40 ,  G06N5/04 ,  G06N20/00 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06Q30/0241 ,  G06Q30/0251

CPC classification number: G06Q30/0244 ,  G06F40/40 ,  G06N5/04 ,  G06N20/00 ,  G06Q30/0201 ,  G06Q30/0202 ,  G06Q30/0264 ,  G06Q30/0276

Abstract: Systems and methods for constraint-based optimization, comprising: an AI demand forecasting engine, an optimization engine, a user-defined objective, and a user-defined set of constraints. Using historical sales data, the AI demand forecasting engine generates a plurality of entities, each entity defined by a placement of an item in a promotion platform; and forecasts the objective associated with each entity. The optimization engine generates a plurality of plans, each plan consisting of a unique subset of entities. Plans that violate at least one constraint are eliminated by the optimization engine, leaving a set of candidate solutions. An optimum plan is selected from the set of candidate solutions based on maximization of the objective.

公开(公告)号：US12118482B2

公开(公告)日：2024-10-15

申请号：US17153257

申请日：2021-01-20

Applicant: Kinaxis Inc.

Inventor： Brian Keng ,  Anneya Golob ,  Yifeng He

IPC: G06Q10/04 ,  G06F17/11 ,  G06F18/21 ,  G06N7/01 ,  G06Q10/0637

CPC classification number: G06Q10/04 ,  G06F17/11 ,  G06F18/217 ,  G06N7/01 ,  G06Q10/0637

Abstract: A system and method for optimizing an objective having discrete constraints using a dataset, the dataset including a plurality of aspects associated with the objective. The method comprising: receiving the dataset, the objective, and constraints, at least one of the constraints comprising discrete values; receiving a seed solution comprising initial values for the at least the constraints; iteratively performing until a predetermined threshold is reached: determining a constraint space for each of the constraints have discrete values using a determination of a constraint satisfaction problem; determining an optimized value of the objective using an optimization model, the optimization model taking as input the dataset and the constraint space; and outputting the optimized objective.