Systems and methods for machine-learning assisted inventory placement
First Claim
1. A computer-implemented system for managing inventory placement, the system comprising:
- a memory storing instructions; and
at least one processor configured to execute the instructions to;
receive, from a remote system, an identifier of a product for inventory placement;
determine, based on historical shipment data stored in a database, a region with the highest customer demand for the product;
predict, using a machine learning algorithm, a product tag associated with the product based on at least a temperature associated with the region with the highest customer demand for the product;
modify the database to assign the product tag to the product identifier; and
assign the product for placement in a fulfillment center, wherein the fulfillment center is associated with a fulfillment center tag corresponding to the product tag.
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Abstract
The embodiments of the present disclosure provide systems and methods for managing inventory placement, comprising a memory storing instructions and at least one processor configured to execute the instructions. The processor may be configured to receive an identifier of a product for inventory placement, and determine, based on historical shipment data stored in a database, a region with the highest customer demand for the product. The processor may predict, using a machine learning algorithm, a product tag associated with the product based on at least a temperature associated with the region with the highest customer demand for the product. The processor may further modify the database to assign the product tag to the product identifier, and assign the product for placement in a fulfillment center. The fulfillment center may be associated with a fulfillment center tag corresponding to the product tag assigned to the product.
26 Citations
20 Claims
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1. A computer-implemented system for managing inventory placement, the system comprising:
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a memory storing instructions; and at least one processor configured to execute the instructions to; receive, from a remote system, an identifier of a product for inventory placement; determine, based on historical shipment data stored in a database, a region with the highest customer demand for the product; predict, using a machine learning algorithm, a product tag associated with the product based on at least a temperature associated with the region with the highest customer demand for the product; modify the database to assign the product tag to the product identifier; and assign the product for placement in a fulfillment center, wherein the fulfillment center is associated with a fulfillment center tag corresponding to the product tag. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A computer-implemented method for managing inventory placement, the method comprising:
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receiving, from a remote system, an identifier of a product for inventory placement; determining, based on historical shipment data stored in a database, a region with the highest customer demand for the product; predicting, using a machine learning algorithm, a product tag associated with the product based on at least a temperature associated with the region with the highest customer demand for the product; modifying the database to assign the product tag to the product identifier; and assigning the product for placement in a fulfillment center, wherein the fulfillment center is associated with a fulfillment center tag corresponding to the product tag. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
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20. A computer-implemented system for managing inventory placement, the system comprising:
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a memory storing instructions; and at least one processor configured to execute the instructions to; receive, from a remote system, an identifier of a product for inventory placement; determine, based on historical shipment data stored in a database, a region with the highest customer demand for the product; predict, using a classification model, a product tag associated with the product based on at least a temperature associated with the region with the highest customer demand for the product; modify the database to assign the product tag to the product identifier; store information associated with the product in the database, the information comprising the product tag assigned to the product and the product identifier; train the classification model to automatically assign product tags to new products, based on the information stored in the database; identify a fulfillment center associated with a fulfillment center tag that matches the product tag, wherein; the fulfillment center tag is indicative of a temperature associated with a location of the fulfillment center; and identifying the fulfillment center comprises determining at least one of maximum capacity or building restriction associated with the fulfillment center; modify the database to assign the product for placement in the identified fulfillment center; and evaluate at least one of the product tag or the fulfillment center tag periodically, wherein evaluating at least one of the product tag or the fulfillment center tag comprises; determining the temperature associated with at least one of the product tag or the fulfillment center tag; determining an actual temperature associated with at least one of the region with the highest customer demand for the product or the location of the fulfillment center; calculating a difference between the temperature with the actual temperature; and replacing at least one of the product tag or the fulfillment center tag with a new tag when the difference exceeds a predetermined threshold.
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Specification