公开(公告)号：US11836654B2

公开(公告)日：2023-12-05

申请号：US17306766

申请日：2021-05-03

Applicant: Amazon Technologies, Inc.

Inventor： Senmao Liu ,  Jose Ramon Algara Allegre ,  Rowan William Hale ,  Eric M. Hayward ,  Ziyan Huang ,  Jingnan Li ,  Robert Dreaper McDonald, Jr. ,  Carl Morris ,  Wilko Ziggy Schulz-Mahlendorf ,  Sharath Selvaraj ,  Kreethigha Thinakaran

IPC: G06Q10/0631 ,  G06Q10/0835 ,  G06Q50/28 ,  G06Q10/083 ,  G06N20/00 ,  G06Q10/04

CPC classification number: G06Q10/06311 ,  G06N20/00 ,  G06Q10/0835 ,  G06Q10/0838 ,  G06Q50/28 ,  G06Q10/04

Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.

公开(公告)号：US20210326788A1

公开(公告)日：2021-10-21

申请号：US17306766

申请日：2021-05-03

Applicant: Amazon Technologies, Inc.

Inventor： Senmao Liu ,  Jose Ramon Algara Allegre ,  Rowan William Hale ,  Eric M. Hayward ,  Ziyan Huang ,  Jingnan Li ,  Robert Dreaper McDonald, JR. ,  Carl Morris ,  Wilko Ziggy Schulz-Mahlendorf ,  Sharath Selvaraj ,  Kreethigha Thinakaran

IPC: G06Q10/06 ,  G06Q10/08 ,  G06Q50/28 ,  G06N20/00

Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.

公开(公告)号：US11010697B1

公开(公告)日：2021-05-18

申请号：US15896872

申请日：2018-02-14

Applicant: Amazon Technologies, Inc.

Inventor： Senmao Liu ,  Jose Ramon Algara Allegre ,  Rowan William Hale ,  Eric M. Hayward ,  Ziyan Huang ,  Jingnan Li ,  Robert Dreaper McDonald, Jr. ,  Carl Morris ,  Wilko Ziggy Schulz-Mahlendorf ,  Sharath Selvaraj ,  Kreethigha Thinakaran

IPC: G06Q10/06 ,  G06Q10/08 ,  G06Q50/28 ,  G06N20/00 ,  G06Q10/04

Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.