Walmart Apollo, LLC

Chittaranjan Tripathy

Ioannis Pavlidis

Abhijeet Rajendra Phatak

Kamal Manglani

Karan Khurana

Sriram Krishnaswamy

Ashwin Sureshkumar

Faraz Hussain

Ajaykartheek Vasagiri

Siddharth Pratap Singh

Rekha Venkatakrishnan

Kaiyi Zhang

Aaron Martin John Sharpe

Rishabh Mudgal

Christopher Grierson

A customer order prediction system can include a computing device configured to obtain customer order data characterizing a customer's interaction with an electronic marketplace and to obtain environmental data characterizing at least one event expected to effect the customer's ordering behavior. The computing device can be further configured to generate feature data based on the customer data and the environmental data wherein the feature data organizes the customer data and the environmental data based on characteristics of an order size estimation model. The computing device is also configured to determine a predicted customer order size using the order size estimation model and to adjust a delivery availability of the electronic marketplace based on the predicted order size.

Methods and apparatuses for automatically estimating order sizes

A delivery route planning system can include a computing device configured to obtain order delivery data that includes information characterizing delivery locations and delivery time windows associated with a first plurality of orders and to determine a delivery plan based on the order delivery data. The computing device can be further configured to identify recyclable time in the delivery time and to obtain supplemental order delivery data that includes information characterizing supplemental orders characterizing delivery locations and delivery time windows associated a second plurality of orders. The computing system can add one or more supplemental order deliveries from the second plurality of orders to the delivery plan based on the recyclable time, the supplemental order delivery data and at least one predetermined delivery constraint.

Methods and apparatuses for adding supplemental order deliveries to delivery plans

This application relates to automatically scheduling timeslots, such as timeslots for scheduling item pickups and deliveries. The embodiments may employ machine learning process to determine, for each of a plurality of timeslots, a timeslot capacity. The embodiments may further determine a time as to when each of the plurality of timeslots become available for selection, such as on a webpage. In some examples, the time determined to make available for selection each of the plurality of timeslots is based on a predetermined amount of time before the timeslot. Further, the embodiments may provide for display each of the plurality of timeslots at the determined time. The embodiments may further include receiving a selection of one of the plurality of timeslots, and scheduling a pickup or delivery based on the selected timeslot. The machine learning processes may be trained with features generated from historical timeslot data and workforce availability.

Methods and apparatus for scheduling timeslots using machine learning processes

This application relates to apparatus and methods for automatic delivery route generation and assignment. In some examples, a computing device determines delivery locations for each of a plurality of previous routes taken by each of a plurality of drivers over a period of time. The computing device also obtains a plurality of current routes to be assigned to the plurality of drivers. Further, the computing device determines a familiarity value for each of the plurality of drivers for each of the plurality of current routes based on the delivery locations of the previous routes taken by each driver. The computing device assigns each of the plurality of drivers to a current route based on the determined familiarity values, and stores the assignments in a data repository. In some examples, the computing device transmits the assignments to another computing device, such as a computing device of each driver.

Methods and apparatus for automatic route assignment

This application relates to apparatus and methods for automatically providing item reviews. In some examples, a website provides a widget on a website allowing a customer to request an item review for an item. In response to the customer requesting the item review, a computing device determine whether suitable reviews for the item are available. If suitable reviews are available, the reviews are provided to the customer requesting the item review. If suitable reviews are not available, the computing device determines a set of customers to request item reviews for the item from, and provides item review requests to the determined set of customers. The computing device receives responses to the item review requests received from the set of customers, and provides an item review based on the received item review requests. In some examples, the website provides the item review to the customer requesting the item review.

Methods and apparatus for automatically providing item reviews and suggestions

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Sunnyvale, CA, United States of America

Chittaranjan Tripathy