Walmart Apollo, LLC

Zum Services, Inc.

Amazon Technologies, Inc.

Rohit Jain

Deepak R Deshpande

Abhishek Garg

Andrew Mormysh

Melissa Shiu

Sidi Liu

Vidyanand Krishnan

Pratosh Deepak Rajkhowa

Pratosh D Rajkhowa

Gustavo Ocasio

Niket Sanghvi

Mingang Fu

Ameya Ajay Shendre

Pavan Kumar

Shekhar Gupta

Amritayan Nayak

Puneet Srivastava

Lipi Sanghi

Sneha Narahalli Balasubramanya

Anurag Gupta

Madhavan Kandhadai Vasantham

Austin Lee Smith

Arun Prasad Nagarathinam

Prakash Seetharaman

Manish Kumar Dalmia

Srinivasan Venkatesan

Alberto Milan Gutierrez

Pushkar Raj Pande

Syed Aman

Thomas Luke Kovarik

David Charles Couvrette

Rashmi Choudhary

Constantine Gerasimovich

Surnaik Prakash Srivastava

Chika Ugboh

Mary Kay Bowman

Mary Katherine Bowman

Dinoop Dayanand

Shanmuga Sundaram

Avaneesh Tiwari

Nitin Agrawal

Vikram Bhogayta

Mihir Vijay Bendale

Teng Yi

Elsie Nallipogu

Raymond Solyne Matthieu, Iii

Benjamin McDougall Hartung

Shiva Nagabushanaswamy

Alexey Kononov

Sreejith Nair

Kanstantsin Gerasimovich

Karan Verma

Zekariyas Kassa Gebru

Eileen Tracey Quenin

Navkaran Singh Chadha

Nitish Sarin

Yiren Ye

Vineet Wason

Kumar Malyala

Felipe Duarte

Roberto Moura

Sneha Narahalli

Hagit Katzenelson

Richard D Hunt

Kurt Harold Zumwalt

Sergey Gavrilov

Nitesh Goyal

Srinivas K Rao

A system and method include a device associated with a user. The device may identify to a server computer a route to be reassigned from a first vehicle to a second vehicle among a fleet of vehicles. The server device may include an artificial intelligence engine which compares the route to be reassigned to a plurality of route groups associated with one of the administrator and the ride requestor. The server device may further identify one or more route groups which are able to service the route to be reassigned based on the artificial intelligence engine. The server device may transmit a graphical representation of one or more of the plurality of route groups which is proximally available in terms of location and time, as determined by the artificial intelligence engine to service the route to be reassigned with a color coded indicator. The server device reassigns the route.

Route stacking in a fleet routing system

This application relates generally to third party carrier management by a shipper of items. These items may be ordered and shipped by the shipper to a distribution center with final delivery performed by the third party carrier. In an embodiment, a system includes at least one processor operatively coupled with a datastore, the at least one processor configured to: send a bid inquiry to a first carrier device and a second carrier device; receive first bid information responsive to the bid inquiry from the first carrier device; receive second bid information responsive to the bid inquiry from the second carrier device; determine a common delivery condition set of the first bid information and the second bid information; and select the first carrier device over the second carrier device based on the common delivery condition set of the first bid information and the second bid information.

Third party carrier management

A system and method include a server computer that determines a plurality of routes and corresponding route schedules for a plurality of ride service requests. The server computer assigns a plurality of vehicles to service each one of the plurality of routes and further assigns one of the plurality of vehicles to one of a plurality of drivers to perform the route according to the route schedule. The server computer may detect an exception to the route schedule, identify a resolution to the exception, and automatically implement the resolution to the exception.

Fleet routing control system and method

A system for rush order fulfilment optimization is discussed. The system includes mobile devices that are each associated with a worker and a rush fulfillment engine executed by a computing system which dynamically updates a task queue of each worker upon receipt of a new rush order according to a task completion rate difference between an estimated task completion rate and the current task completion rate of the worker.

Systems and methods for rush order fulfilment optimization

A system and method include providing a list of children to be picked up by a vehicle at a particular stop along a route to a driver device. The provided list is displayed as part of a graphical user interface which includes a plurality of pick up options for each child in the list of children. The options include a picked up interface button, a no show interface button and a canceled button. The graphical user interface provides a picture and identification of each child. The server device transmits a message to a user device with confirmation that a child has been picked up. The server device also provides a list of children to be dropped off by the vehicle via a graphical user interface that also provides drop off options for each child in the list of children including a dropped off button or an on hold button.

Student custody monitoring and tracking in a fleet routing system

A system and method that includes a ride requestor device, a driver device, a server device, and a user device is disclosed. The ride requestor device provides rider information and stop location information for a plurality of riders. The driver device provides location information, navigation information, and stop timing information for a particular vehicle in a fleet of vehicles. The server device includes an artificial intelligence engine which generates and optimizes a plurality of routes for service by the fleet of vehicles to provide a ride to each one of the plurality of riders.

Fleet routing system and method

A graphical user interface and a system are provided which include a route identification interface element which specifies a new route for a vehicle, a plurality of route type buttons, a vehicle type interface, a stop order interface, a map, a control button, and an assignment button. The stop order interface identifies one or more stops for a vehicle in a fleet of vehicles. The map identifies the new route and the one or more stops graphically on the graphical user interface. The control button provides a utilization view for the one or more vehicles in the fleet of vehicles from which a vehicle from the one or more vehicles in the fleet of vehicles that are available can be assigned to the new route.

User interface for fleet routing system

A method being implemented via execution of computing instructions configured to run at one or more processors. The method can include determining a primary store and one or more secondary stores for pickup of an order of a user, based at least in part on a pickup type of the order. The method also can include determining real-time availabilities of first time slots at the primary store and real-time availabilities of second time slots at the one or more secondary stores. The method additionally can include generating a list of available time slots comprising at least a portion of the first time slots at the primary store and at least a portion of the second time slots at the one or more secondary stores, based at least in part on the real-time availabilities of the first time slots at the primary store and the real-time availabilities of the second time slots at the one or more secondary stores. The method further can include facilitating displaying to the user a user interface comprising at least a portion of the list of available time slots. Other embodiments are described.

Automatically merging pickup and delivery time slots from nearby stores

Horizontally-scalable systems and methods for scheduling and optimizing deliveries are described herein. At least one scheduler is configured to receive a request to schedule a delivery for an origination location. The request includes a desired time slot. The request is compared to a persistent delivery snapshot for the origination location to determine availability of the desired time slot. An interim delivery snapshot including the requested delivery is generated when the persistent delivery snapshot has an available time slot corresponding to the desired time slot. At least one optimizer is configured to receive the interim delivery snapshot and generate an updated persistent delivery snapshot by applying an optimization process to the interim delivery snapshot.

Systems and methods for combinatorial resource optimization

Systems and methods for rush order fulfillment optimization

This application relates to apparatus and methods for batching orders for delivery. In some examples, a computing device may obtain order data identifying at least a first order and a second order. The computing device may determine whether the first order can be delivered to a first delivery address and the second order can be delivered to a second delivery address within a delivery time window. Based on the determination, the computing device may batch the first order and the second order to generate a batched order. In some examples, the computing device determines if the delivery vehicle can store the items for the first order and the second order to determine whether the orders may be batched. The computing device may generate assignment data identifying an assignment of the batched order to a delivery vehicle, and may transmit the assignment data to another computing device.

Systems, non-transitory computer readable mediums, and methods for grocery order batching and customer experience

In some examples, a system may include a memory resource storing instructions, and one or more processors. In various examples the one or more processors may be configured to execute the instructions to receive data indicating that an order has been dropped by a driver of a first computing system. The order may include a set of order parameters that may include a first order parameter and a second order parameter. Additionally, the one or more processors may be configured to execute the instructions to determine a remaining delivery time period based at least a time when the order was dropped and the first order parameter. Moreover, the one or more processors may be configured to execute the instructions to obtain profile data of a set of drivers that includes availability data indicating the corresponding driver is available for assignment. Furthermore, the one or more processors may be configured to execute the instructions to, based on the set of order parameters, the remaining delivery time period and the profile data, implement a set of processes that identify, from the set of drivers, one or more candidate drivers for the order.

System and method of delivery assignment

This application relates to apparatus and methods for determining, assigning, and displaying order deliveries. In some examples, a computing device may obtain order data identifying at least one order for delivery during a timeslot. The computing device may transmit, to a driver's computing device, a request for deliveries for a first price during the timeslot. The computing device may receive, from the driver's computing device, a response accepting the request. The computing device may then assign the driver to the order, and determine a delivery status based on the assignment of the first driver to the first order. The delivery status may identify, for example, that the order has been assigned to the driver, an estimated delivery time, the number of items being delivered, the weight of the items, and a route taken by the driver. The computing device may also display the delivery status.

Method and apparatus for delivery order dispatch and assignment

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.

A system is provided and generally includes a server (e.g., application server), an associate computing device, and a client computing device. The server can receive a user arrival notification that indicates a user has arrived to pick up purchased goods. The server can transmit a scan initiation request to a remote terminal that causes the remote terminal to scan at least one network. The server can receive scan data for the scanned network from the remote terminal indicating, for example, a signal strength of that network. The server can determine a current wait time based on the received scan data for the scanned network, and can transmit the current wait time to the remote terminal.

Method and apparatus for predicting wait times

Growing community of inventors

Sunnyvale, CA, United States of America

Rohit Jain