在庫管理および最適化のためのシステムおよび方法

Title:

在庫管理および最適化のためのシステムおよび方法

Document Type and Number:

Japanese Patent JP7426388

Kind Code:

B2

Abstract:

The present disclosure provides systems and methods that may advantageously apply machine learning to accurately manage and predict inventory variables with future uncertainty. In an aspect, the present disclosure provides a system that can receive an inventory dataset comprising a plurality of inventory variables that indicate at least historical (i) inventory levels, (ii) inventory holding costs, (iii) supplier orders, and/or (iv) lead times over time. The plurality of inventory variables can be characterized by having one or more future uncertainty levels. The system can process the inventory dataset using a trained machine learning model to generate a prediction of the plurality inventory variables. The system can provide the processed in inventory dataset to an optimization algorithm. The optimization algorithm can be used to predict a target inventory level for optimizing an inventory holding cost. The optimization algorithm can comprise one or more constraint conditions.

Inventors:

Allson, Henrik
Bellara, Gotham
Koshfetrat Pacazad, Sina
Banerjee, Divyajiyoti
Krishnan, Nikhill

Application Number:

JP2021523893A

Publication Date:

February 01, 2024

Filing Date:

October 31, 2019

Export Citation:

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Assignee:

C 3. AI, Incorporated

International Classes:

G06Q10/04; G06Q10/087

Domestic Patent References:

JP2007226718A
JP2009042810A
JP2006503352A

Foreign References:

US20040153187
US20170185933
US20180285902
US20140031966
US5287267

Attorney, Agent or Firm:

Shusaku Yamamoto
Natsuki Morishita
Takatoshi Iida
Daisuke Ishikawa
Kensaku Yamamoto

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