公开(公告)号：US20240242145A1

公开(公告)日：2024-07-18

申请号：US18156347

申请日：2023-01-18

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Haochen Luo ,  Eric Hermann ,  Rishab Saraf ,  Abhinav Darbari ,  Teodor Lefter ,  Jason Sanchez ,  Jagannath Putrevu

IPC: G06Q10/0631 ,  G06Q10/0639 ,  G06Q10/0835 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0601

CPC classification number: G06Q10/063118 ,  G06Q10/06398 ,  G06Q10/08355 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0635

Abstract: An online concierge shopping system fulfills orders using workers who pick items at a warehouse to complete an order and workers to deliver the orders to a customer's location. To optimize the staffing of workers for each task, the system uses a trained model to predict the number of workers needed to achieve an optimal outcome based on an input set of contextual information. The system also schedules specific workers to various shifts using the predicted number of workers needed and then searching a feasibility space for an optimal solution. The trained model may be updated based on performance observations.

公开(公告)号：US20240362580A1

公开(公告)日：2024-10-31

申请号：US18141394

申请日：2023-04-29

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Kenneth Jason Sanchez ,  Haochen Luo ,  Rishab Saraf ,  Eric Hermann ,  Dario Fidanza

IPC: G06Q10/087 ,  G06Q30/0202

CPC classification number: G06Q10/087 ,  G06Q30/0202

Abstract: An online system evaluates different item assortments for a physical warehouse having limited capacity to stock items. Each item assortment is stocked at the physical warehouse in proportion to an assortment split weight. The items at the warehouse are available for users to order, for example to be gathered by a picker and physically delivered to users near the warehouse. Rather than display all items actually stocked at the physical warehouse to all users, the different item assortments are displayed to different users. Users may order items from the assigned item assortment and, because both item assortments are actually stocked at the physical warehouse, orders from either item assortment may be successfully fulfilled for delivery. The different user interfaces thus permit evaluation of the preferred item assortment by users while maintaining expected delivery capability and while using the same storage capacity of the physical warehouse.

公开(公告)号：US20240070603A1

公开(公告)日：2024-02-29

申请号：US17899977

申请日：2022-08-31

Applicant: Maplebear Inc. (dba Instacart)

Inventor： Jagannath Putrevu ,  Haochen Luo ,  Xiangpeng Li ,  Rishab Saraf

IPC: G06Q10/08 ,  G06F16/29 ,  G06Q30/02

CPC classification number: G06Q10/08355 ,  G06F16/29 ,  G06Q30/0205

Abstract: A grid is created for a map of a geographic region based on a location planning request received from a user device. A plurality of candidate cells are identified from among a plurality of cells of the grid. Each of the candidate cells including a candidate location for a warehouse. Respective isochrones are generated relative to the candidate locations of the plurality of candidate cells based on a delivery time threshold indicated in the location planning request. Respective isochrone scores are determined for the generated isochrones based at least on data indicating a past volume of sales in the isochrone. Based on the respective isochrone scores of the candidate locations, a subset of the candidate locations is selected as a recommended set of locations for warehouses to cover the geographic region. A notification indicating the recommended set of locations is transmitted to the user device.

公开(公告)号：US12288172B2

公开(公告)日：2025-04-29

申请号：US18156347

申请日：2023-01-18

Applicant: Maplebear Inc.

Inventor： Haochen Luo ,  Eric Hermann ,  Rishab Saraf ,  Abhinav Darbari ,  Teodor Lefter ,  Kenneth Jason Sanchez ,  Jagannath Putrevu

IPC: G06Q10/0631 ,  G06Q10/0639 ,  G06Q10/0835 ,  G06Q10/087 ,  G06Q30/0202 ,  G06Q30/0601

Abstract: An online concierge shopping system fulfills orders using workers who pick items at a warehouse to complete an order and workers to deliver the orders to a customer's location. To optimize the staffing of workers for each task, the system uses a trained model to predict the number of workers needed to achieve an optimal outcome based on an input set of contextual information. The system also schedules specific workers to various shifts using the predicted number of workers needed and then searching a feasibility space for an optimal solution. The trained model may be updated based on performance observations.