Grubhub Holdings Inc.

Other

Ryan J O'Neil

Sagar Sahasrabudhe

Gregory Danko

Carolyn Mooney

Technologies for computing, within a real-time time interval, of a digital plan for a vehicle in response to receipt by an online system of a volume of short-route pickup-and-delivery requests that increases over an operational period, include: receiving, by a hybrid optimization model, a set of digital inputs; where the set of digital inputs includes (i) pairs of geo-location data associated with pickup-and-delivery requests and (ii) geo-location data associated with the vehicle and (iii) precedence data that indicate an order that geo-locations in a pair of geo-location data are to be visited; using the hybrid optimization model to generate, in an execution time that does not exceed the real-time time interval, a pickup and delivery plan that conforms to the precedence data as digital output in response to the set of digital inputs; where the hybrid optimization model includes a constraint programming-based solver that operates in coordination with at least one other solver; creating, digitally storing, transmitting, and causing display of the digital output on a display of a device that is associated with the vehicle.

Fast computational generation of digital pickup and delivery plans

A computer-implemented method comprises receiving training data corresponding to a plurality of trips, the training data including at least a value for a set of attributes for each of the plurality of trips, the set of attributes including an indication of when in a week a trip is taken or in which of a plurality of meal-based time zones in a day the trip is taken, the training data including an actual travel time for each of the plurality of trips. The method further comprises creating and storing, in computer memory, a digital model that is configured to predict a travel time for a future trip based on the training data, the digital model including a set of parameters corresponding to the set of attributes, the digital model including a plurality of sets of values for the set of parameters. In addition, the method comprises receiving specific data for a specific trip, the specific data including an indication when in a week the specific trip will be taken or in which of a plurality of meal-based time zones of a day the specific trip will be taken; calculating a specific travel time for the specific trip using the digital model; determining a specific prediction interval for the specific travel time based on the plurality of sets of values for the set of parameters; and causing display of the specific travel time and the specific prediction interval.

Prediction of travel time and determination of prediction interval

Disclosed is a split conduit for separating line and low voltage wiring, wherein two wire or cable types are supported and do not interfere with one another along the conduit length. The conduit includes a rounded outer wall forming an enclosed cross section, wherein a partition is provided within the interior of the conduit that runs along its length to create a first and second pathway. The outer surface of the conduit is discretely marked based on line or low voltage, allowing a user to distinguish what wire type is in each pathway and to locate the partition without inspecting the wires or looking into the interior of the conduit. The split conduit is adapted to be connected to a split meter socket box having a divider for separating connection types, wherein wires from corresponding conduit chambers can be oriented appropriately to establish electrical connectivity within the meter box.

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Washington, DC, United States of America

Ryan J O'Neil