Amazon Technologies, Inc.

Robert Dreaper McDonald, Jr

Udit Madan

David Daniel Glick

Michael Ellsworth Bundy

Jose Ramon Algara Allegre

Ziyan Huang

Wilko Ziggy Schulz-Mahlendorf

Kreethigha Thinakaran

Carl Morris

Sharath Selvaraj

Senmao Liu

Jingnan Li

Rowan William Hale

Eric M Hayward

Eric C Young

Ranganath Atreya

Arun Ponniah Sethuramalingam

Jun Zhao

Sameer Vinod Shah

Hao He

Srinivas Palla

Eitan S Levi

Samir Kumar

Matthew Rice Carlson

Kevin R MacKenzie

Kinsley O Ogunmola

Jai Modi

Babitha Achutha

Facundo Leonardo Agriel

Vishal Nandkishor Patel

Matthew S Dingfield

Michael A Shaver

Maitreyi Nanjanath

Lubos Bosak

Nathan Ryan Bosch

Steven Michael Hood

Sujeevan Rajayogam

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.

On-demand resource scheduling

Various embodiments of a system and method for labor allocation across distinct processes of a materials handling facility are described. Embodiments may include a computer system configured to generate a model of a materials handling facility. The model may indicate, for each of multiple distinct quantities of work processed via a respective materials handling process, a quantity of labor resources processing that quantity of work in accordance with the respective materials handling process. The computer system may evaluate the model to determine that one or more additional labor resources are needed to process a particular quantity of work in accordance with a particular materials handling process. The computer system may select a labor resource processing a different quantity of work in accordance with a different materials handling process and generate an instruction that directs that labor resource to process the particular quantity of work via the particular materials handling process.

System and method for resource allocation across distinct processes of a materials handling facility

This disclosure describes a system and method for utilizing an automated aerial vehicle for rapidly transporting a priority pick item when an exception occurs (e.g., an item that was to be picked from another location or otherwise processed is found to be missing or damaged). In some implementations, a priority pick instruction may be generated that directs picking of the item from an alternative location after which the item may be transported by the automated aerial vehicle to a processing location (e.g., a problem solve station). A flight path may be determined which may have starting and ending points at designated locations where the automated aerial vehicle can safely land and take off for acquiring and/or delivering the priority pick item.

Utilizing automated aerial vehicles for transporting priority pick items

Disclosed are various implementations for generating one or more visualization regions in a user interface indicative of a state of a fulfillment center. A visualization region may be generated comprising one or more visual identifiers, labels, and metrics describing one or more stages in a fulfillment process. In response to a manipulation of a portion of the visualization region, a predefined action may be initiated.

Item flow visualization for outbound fulfillment

A conferencing system receives information identifying a user and retrieves calendar information specifying scheduled events of the user. The conferencing system selects one of the events and joins the user to the event without the user manually entering information about the event.

Automatic conference call connection

Various embodiments of a system and method for allocating labor to units processed in a materials handling facility are described. Embodiments may include a labor allocation system configured to receive information associated with a materials handling process that includes handling multiple units. For each unit, such information may indicate a respective pre-handling time period and a respective post-handling time period. The labor allocation system may determine a measure of variability of the pre-handling time periods associated with the units. The labor allocation system may also determine a measure of variability of the post-handling time periods. In response to determining that one of the measures of variability is less than the other, the labor allocation system may determine that each time period associated with the lesser measure of variability is representative of a quantity of labor expended to process a respective unit in accordance with the materials handling process.

System and method for allocating labor to units processed in a materials handling facility

Growing community of inventors

Seattle, WA, United States of America

Robert Dreaper McDonald, Jr