公开(公告)号：US20250139648A1

公开(公告)日：2025-05-01

申请号：US18498624

申请日：2023-10-31

Applicant: Walmart Apollo, LLC

Inventor： Jiahao Zhang ,  Raisa Mukadam ,  Karun Dhingra

IPC: G06Q30/0202 ,  G06Q10/087 ,  G06Q30/0201

Abstract: Examples provide for generating dynamic minimum presentation (MP) values for optimizing fresh item production while reducing system resource usage. An MP engine calculates a monetary level impact of overproduction and underproduction of a fresh item using production-related data, including a shelf life of the fresh item and cost of production. The calculated monetary level impact includes predicted monetary loss from lost sales due to an item going out-of-stock and/or monetary loss from unsold instances of the fresh item where too many instances of the fresh item are prepared. The dynamic MP value is generated based on dynamic data, the item attribute data, and the predicted monetary loss. The dynamic MP value is used to create a production plan recommendation customized at a store-item level for a selected date, thereby enabling optimization of safety stock while minimizing system resource usage consumed in generating MP predictions for fresh items.

公开(公告)号：US20240265366A1

公开(公告)日：2024-08-08

申请号：US18106167

申请日：2023-02-06

Applicant: Walmart Apollo, LLC

Inventor： Ravi Kiran Songa ,  Surbhi Dhariwal ,  Raisa Mukadam ,  Darshini Priya Konanki ,  Nhu Quy Nguyen ,  Brandy L. Metzner ,  Rahul Jain ,  Veera Kishon Kumar Mucherla

IPC: G06Q20/20 ,  G06N20/00

CPC classification number: G06Q20/202 ,  G06N20/00

Abstract: Some embodiments provide systems comprises: a customer database; a product database; a training data database; a customer evaluation system configured to implement one or more machine learning acceptance probability models to identify an acceptance likelihood factor, and determine whether the each respective customer has a corresponding acceptance likelihood factor greater than a likelihood threshold value; and a plurality of point of sale (POS) systems configured to complete sales transactions, obtain customer identifying information, and communicate the customer identifying information to the customer evaluation system; wherein the customer evaluation system is configured to communicate customer information to the payment method offer entity when the customer has an acceptance likelihood factor greater than a likelihood threshold value, receive authorization to present the customer with a payment method offer, and to present the payment method offer.