Walmart Apollo, LLC

Aditya Arcot Srinivasan

Mingang Fu

Seon Ki Kim

Madhavan Kandhadai Vasantham

Jing Huang

Ou Sun

A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform: determining that a respective number of totes for a respective order of one or more orders can be reduced; reducing, using an infeasible totes loop, the respective number of the totes for the respective order to a respective reduced number of the totes; executing, as part of the infeasible totes loop, an item search; running the item search until a predefined number of iterations is reached; generating directions for a route of a pick walk based on a map of a retail facility; and facilitating displaying, on an electronic device, the route of the pick walk on the map of the retail facility. Other embodiments are disclosed herein.

Systems and methods for optimization of pick walks

A system includes one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform: selecting, by a greedy tote reduction algorithm within an infeasible totes loop, items that have a highest volume restriction and a highest weight restriction for each of a plurality of respective totes; iteratively executing a swap of the items; iteratively searching for candidate solutions until a solution of picklists for the plurality of respective totes containing the items, as swapped, is found; executing a minimum trolley loop algorithm on the solution of picklists to create combined picklists; and displaying to a picker on an interface of a computing device, turn-by-turn directions within a pick walk for the combined picklists. Other embodiments are disclosed herein.

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 cause the one or more processors to perform receiving one or more orders comprising a list of one or more pallets; grouping each pallet of the one or more pallets into one or more groups using one or more respective qualities of each respective pallet; for each group of the one or more groups, building one or more stacks of pallets using at least three different stacking models; selecting a final stack list of a model of the at least three different stacking models having a lowest number of stacks; and optimizing the final stack list using a probabilistic model. Other embodiments are disclosed herein.

Systems and methods for vehicle routing

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 respective number of totes for each respective order of one or more orders; determining, using a first set of rules, when the respective number of totes for a respective order of the one or more orders can be reduced; when the respective number of totes is determined to be able to be reduced, reducing, using a second set of rules, the respective number of totes for the respective order to a respective reduced number of totes for the respective order of the one or more orders; comparing the respective number of totes for the respective order to the respective reduced number of totes for the respective order; and when the respective number of totes for the respective order is compared to be equal to the respective reduced number of totes for the respective order, facilitating displaying, on an electronic device to a picker, the respective number of totes for the respective order. Other embodiments are disclosed herein.

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: executing a greedy incremental batcher loop, which can comprise: selecting a first picklist of one or more picklists; and merging the first picklist with one or more picklists in a first remainder of the one or more picklists when the merging would decrease a cost of the first picklist, wherein the first remainder of the one or more picklists comprises the one or picklists excluding the first picklist; executing a randomized tote local search loop, which can comprise: selecting two random picklists of the one or more picklists, as merged; and swapping totes of the two random picklists of the one or more picklists, as merged, when the swapping would decrease a cost of at least one picklist of the two random picklists; executing an update min trolley loop, which can comprise: selecting a shortest picklist of the one or more picklists, as merged and swapped; and combining the shortest picklist with at least one picklist of the one or more picklists, as merged and swapped, wherein a combination picklist of the shortest picklist and the at least one picklist results in a savings of cost; and facilitating displaying the combination picklist and the one or more picklists, as merged and swapped, to a picker. Other embodiments are disclosed herein.

Systems and methods for optimizing delivery vehicle resources (e.g. a plurality of vehicles) are described herein. Available time slots for the plurality of vehicles are determined and presented to a user. In response to receiving a delivery order indicating a selected time slot, the delivery order is assigned to a vehicle from the plurality of vehicles based on a time slot indicated in the delivery order and a set of delivery parameters. A delivery route is calculated for each vehicle having a delivery order based on the set of delivery parameters. An optimized delivery route is calculated for each vehicle having a delivery order based on the set of delivery parameters.

Growing community of inventors

Sunnyvale, CA, United States of America

Aditya Arcot Srinivasan