Walmart Apollo, LLC

Kunlei Lian

Mingang Fu

Richard Ulrich

Jing Huang

Jingying Zhang

Dong Xu

Ti Zhang

Ming Ni

Clifford Wayne Bolinger

Liqing Zhang

Shuohao Wu

Yu Zheng

Jackie Lei Guan

A method including obtaining an optimization request at a coordinating engine. The method also can include triggering engines to process the optimization request. At least one of the engines divides the optimization request into subproblems. At least a portion of the engines solve the subproblems. Respective instances of at least one of the engines are triggered to handle respective ones of the subproblems. Each of the engines provides a dynamic algorithmic flow using modularized algorithmic solvers. The dynamic algorithmic flow is adjusted based on a respective input to each of the engines. The method additionally can include outputting, from the coordinating engine, one or more results in response to the optimization request, based on results for the subproblems generated by the engines. Other embodiments are described.

Divide-and-conquer framework and modularized algorithmic scheme for large-scale optimization

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a request to generate one or more schedules for one or more drivers; determining one or more respective day cab schedules for each respective day cab driver of the one or more drivers; assigning one or more permanent drivers of the one or more drivers to one or more permanent tractors; assigning at least one driver of one or more remaining drivers of the one or more drivers to at least one tractor using a first set of rules; generating the one or more schedules for the one or more drivers; and coordinating displaying the one or more schedules for the one or more drivers on an electronic device of a user. Other embodiments are disclosed herein.

Systems and methods for driver scheduling

This disclosure describes a graphics processing unit programmed to generate a sample path for the demand of the one or more products at a store based at least in part on data associated with a historical distribution of the variability of the demand of the one or more products. The graphics processing unit may generate a thread corresponding to a plurality scenarios. The graphics processing unit may execute the thread in parallel to determine one or more parameters for each of the plurality of scenarios for the one or more products. The graphics processing unit may select the one or more parameters generated from the execution of one of the sample paths to minimize the cost. The graphics processing unit may adjust an inventory management system to set an inventory management setting based at least in part on the selection of the one or more parameters.

Systems and methods for safety stock settings using a parallel processing computing architecture

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Bentonville, AR, United States of America

Kunlei Lian