公开(公告)号：US20190147462A1

公开(公告)日：2019-05-16

申请号：US15809609

申请日：2017-11-10

申请人： Target Brands, Inc.

发明人： Shubhankar Ray ,  Saibal Bhattacharya ,  Zeynep Erkin Baz ,  Jagadeesh Balam

IPC分类号： G06Q30/02 ,  G06N99/00

摘要： A computer-implemented method uses sales data to fit static parameters of a demand prediction model that predicts a current demand based in part on a previous demand. The static parameters and the sales data are then used to fit dynamic states of a structural time series model, wherein the dynamic states change over time and are different for different time periods. A time period for a future price is selected and the future price is applied to the structural time-series model using the dynamic states for the time period to generate an expected demand for the time period.

公开(公告)号：US12079828B2

公开(公告)日：2024-09-03

申请号：US17529075

申请日：2021-11-17

申请人： Target Brands, Inc.

发明人： Omar N. Jabri ,  Adam Riggall ,  Duane Sizemore ,  Peter Kim ,  Tikhon Jelvis ,  Yang Liu ,  Saibal Bhattacharya ,  Sayon Majumdar ,  Zeynep Erkin Baz

IPC分类号： G06Q30/02 ,  G06Q10/067 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0601

CPC分类号： G06Q30/0202 ,  G06Q10/067 ,  G06Q10/087 ,  G06Q30/0625

摘要： Methods and systems for forecasting demand for items across multiple channels are disclosed. In some implementations, multi-channel demand forecasting may be performed on a per-item, per-location basis, by selectively generating item-location forecasts for each item and location within a supply chain for each channel, or disaggregating a chain level forecast on a per-item basis to each location. Particular selection of an appropriate model, and selective training of models, allows for efficient computation of such forecasts across a large supply chain with thousands of locations and hundreds of thousands, or millions, of items for which forecasts are generated.

公开(公告)号：US20230153844A1

公开(公告)日：2023-05-18

申请号：US17529075

申请日：2021-11-17

申请人： Target Brands, Inc.

发明人： Omar N. Jari ,  Adam Riggall ,  Duane Sizemore ,  Peter Kim ,  Tikhon Jelvis ,  Claire Liu ,  Saibal Bhattacharya ,  Sayon Majumdar ,  Zeynep Erkin Baz

IPC分类号： G06Q30/02 ,  G06Q10/06 ,  G06Q10/08 ,  G06Q30/06

CPC分类号： G06Q30/0202 ,  G06Q10/067 ,  G06Q10/087 ,  G06Q30/0625

摘要： Methods and systems for forecasting demand for items across multiple channels are disclosed. In some implementations, multi-channel demand forecasting may be performed on a per-item, per-location basis, by selectively generating item-location forecasts for each item and location within a supply chain for each channel, or disaggregating a chain level forecast on a per-item basis to each location. Particular selection of an appropriate model, and selective training of models, allows for efficient computation of such forecasts across a large supply chain with thousands of locations and hundreds of thousands, or millions, of items for which forecasts are generated.