Computer implemented systems and methods for optimization of a product inventory by intelligent distribution of inbound products
AssigneeCoupang Corp.
InventorJe KIM
Life of this patent
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Abstract
Computer-implemented systems and methods for intelligent generation of purchase orders are disclosed. The systems and methods may be configured to: receive an order quantity for a product from a system determining optimal order quantities for products based on demand forecast data; prioritize the order quantity based on actual constraints; and assign the prioritized order quantity to one or more locations.
Claims20
A computer-implemented first system for intelligent distribution of products, the first system comprising:
- a memory storing instructions;
- and
- at least one processor configured to execute the instructions for:
- receiving an order quantity for a product from a second system determining optimal order quantities for products based on demand forecast data, the demand forecast data being generated by a model trained to predict a level of future demand based on at least one of:
- sales statistics, a number of webpage views, a season, a day of the week, or a holiday;
- prioritizing the order quantity based on actual constraints;
- assigning the prioritized order quantity to one or more locations based on current product inventory levels;
- determining an exceeded amount of quantities over an intake capacity of a first location;
- and
- transferring the exceeded amount of quantities to one or more remaining locations in equal amounts across the remaining locations.
A computer-implemented method for intelligent distribution of products, the system comprising:
- receiving an order quantity for a product from a system determining optimal order quantities for products based on demand forecast data, the demand forecast data being generated by a model trained to predict a level of future demand based on at least one of:
- sales statistics, a number of webpage views, a season, a day of the week, or a holiday;
- prioritizing the order quantity based on actual constraints;
- and
- assigning the prioritized order quantity to one or more locations based on current product inventory levels;
- determining an exceeded amount of quantities over an intake capacity of a first location;
- and
- transferring the exceeded amount of quantities to one or more remaining locations in equal amounts across the remaining locations.
A computer-implemented system for intelligent distribution of products, the system comprising:
- a memory storing instructions;
- and
- at least one processor configured to execute the instructions for:
- receiving one or more demand forecast quantities of one or more products, the products corresponding to one or more product identifiers, the demand forecast quantities comprising a demand forecast quantity for each product for each unit of time, and the demand forecast quantities being generated by a model trained to predict a level of future demand based on at least one of:
- sales statistics, a number of webpage views, a season, a day of the week, or a holiday;
- receiving supplier statistics data for one or more suppliers, the suppliers being associated with a portion of the products;
- receiving current product inventory levels and currently ordered quantities of the products;
- determining order quantities for the products based at least on the demand forecast quantities, the supplier statistics data, and the current product inventory levels;
- prioritizing the order quantities based on actual constraints, the actual constraints comprising current product inventory levels;
- assigning the prioritized order quantities to one or more locations;
- determining an exceeded amount of quantities over an intake capacity of a first location;
- transferring the exceeded amount of quantities to one or more remaining locations in equal amounts across the remaining locations;
- and
- generating purchase orders to the suppliers for the products based on the assigned order quantities.
Dependencies are inferred from the claim text.