Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a request for an order comprising one or more items; determining when the order is eligible for batch picking by finding one or more other orders comprising at least one of the one or more items; and when the order is determined to be eligible for batch picking with the one or more other orders: creating one or more clusters by clustering together (1) the at least one of the one or more items of the order and (2) the at least one of the one or more items of the one or more other orders; estimating, for each respective cluster of the one or more clusters, an estimated fulfillment time interval to make ready the order; and assigning each respective cluster of the one or more clusters to at least one respective picker of one or more respective pickers. Other embodiments are disclosed herein.

Abstract: A microelectromechanical systems (MEMS) device and a light assembly that includes the MEMS device. The MEMS device includes a first arm, a second arm, at least one permanent magnet, a fan structure, and a coil. The first arm has a first arm first end and a first arm second end. The second arm is coupled to, and is spaced apart from, the first arm and has a second arm first end and a second arm second end. The at least one permanent magnet is coupled to the first arm second end. The fan structure is coupled to, and extends in cantilever manner from, the second arm second end and includes a connection end and a free end. The coil is disposed on or within the fan structure. When the coil is electrically energized, a Lorentz force is generated that causes the fan structure to vibrate relative to the permanent magnet.

Abstract: A system and method of automated driver selection is disclosed. A plurality of driver profiles and a first order are received. Each of the driver profiles includes at least one driver parameter. The first order includes at least one order parameter. A driver score is calculated for each of the plurality of driver profiles for the first order. The driver score is calculated based on the at least one driver parameter and the at least one order parameter. Each driver profile is ranked based on the calculated driver score and a first delivery assignment request is transmitted to a system associated with a first-ranked driver profile. A response is received to the first delivery assignment request.

Abstract: 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.

Abstract: A system including one or more processors and one or more non-transitory storage media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations including: receiving an order list for delivery at a delivery address; determining an estimated order collection time; continuously monitoring, in real-time, a respective location of each delivery driver of one or more delivery drivers of at least one delivery service by receiving the respective location of each delivery driver of the one or more delivery drivers from a respective delivery driver electronic device of each delivery driver; and instructing a first delivery driver of the one or more delivery drivers to pick up one or more items in the order list and deliver the one or more items to the delivery address. Other embodiments are disclosed herein.

Abstract: Systems and methods including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform functions comprising: determining at least one fleet delivery route for delivery of one or more items of one or more orders to one or more locations using a vehicle fleet; dynamically shuffling the at least one fleet delivery route by at least evaluating a cost differential; when the cost differential satisfies a threshold: removing the first order from the source route; inserting the first order into the first other delivery route; and communicating the first order to a first other deliverer associated with the first other delivery route. Additional embodiments are disclosed herein.

Abstract: 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.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a request from a user; determining, using a regression analysis, an estimated order collection time for a collection of the one or more items of the order list by at least one collector; continuously monitoring a respective location of each respective delivery driver; continuously determining a respective estimated order pickup time for each respective delivery driver; and instructing the first delivery driver of the one or more delivery drivers to pick up the one or more items and deliver the one or more items to the delivery address. Other embodiments are disclosed herein.

Abstract: 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.

Abstract: 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.

Abstract: Systems and methods including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform functions comprising: determining at least one fleet delivery route for delivery of one or more items of one or more orders to one or more locations using a vehicle fleet; dynamically shuffling the at least one fleet delivery route by at least evaluating a cost differential; when the cost differential satisfies a threshold: removing the first order from the source route; inserting the first order into the first other delivery route; and communicating the first order to a first other deliverer associated with the first other delivery route. Additional embodiments are disclosed herein.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a plurality of website orders on a website of an online retailer for delivery of a plurality of products; determining at least one fleet delivery route for delivery of the plurality of products of the plurality of website orders to a plurality of locations using a vehicle fleet of the online retailer; dynamically shuffling the at least one fleet delivery route, wherein dynamically shuffling the at least one fleet delivery route comprises: selecting a source route from the at least one fleet delivery route; selecting a first order of the plurality of web site orders from the source route, the first order scheduled to be delivered to a first location of the plurality of locations; selecting a destination route from (1) the at least one fleet delivery route and (2) one or more third-party delivery routes; evaluati

Abstract: 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.

Abstract: 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.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform receiving a request from a user, wherein the request can comprise: (1) an order list of one or more items; and/or (2) a delivery address for a delivery of the one or more items of the order list to the user; determining, using a regression analysis, an estimated order collection time for a collection of the one or more items of the order list by at least one collector, wherein the regression analysis can use: one or more independent variables affecting the estimated order collection time; respective coefficients of each respective independent variable of the one or more independent variables affecting the estimated order collection time; and/or a constant applicable to the at least one collector; continuously monitoring a respective location of each respective delivery driver of one or more delivery drivers of at least on

Abstract: Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of receiving an order request from a customer, transmitting an order list from the order request to an employee of the store for a collection of products on the order list at the store by the employee, determining an estimated order collection time, continuously monitoring an estimated order pickup time for a delivery driver of a third-party delivery service, and, when the estimated order pickup time for the delivery driver is substantially equal to the estimated order collection time, transmitting a delivery request to the third-party delivery service requesting the delivery driver to pick up the products from the store and deliver the products to the delivery address.

Abstract: 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.

Abstract: A load and route assignment system is provided and generally includes a computing device and a database. The database may store historical inbound load data and historical outbound load data related to previous inbound and outbound loads. The computing device can obtain and aggregate the historical inbound and outbound load data from the database, and determine an optimal path based on the aggregated historical data. The optimal path, along with load attribute data, may be stored in the database as a tour template for future load executions. The computing device may use the tour templates to determine future load assignments to vehicles. The computing device may also obtain real-time load requests, and match them to one or more of a plurality of tour templates. The computing device may assign the matched real-time load requests to a vehicle for execution in accordance with the corresponding load and tour template.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a plurality of website orders on a website of an online retailer for delivery of a plurality of products; determining at least one fleet delivery route for delivery of the plurality of products of the plurality of website orders to a plurality of locations using a vehicle fleet of the online retailer; dynamically shuffling the at least one fleet delivery route, wherein dynamically shuffling the at least one fleet delivery route comprises: selecting a source route from the at least one fleet delivery route; selecting a first order of the plurality of web site orders from the source route, the first order scheduled to be delivered to a first location of the plurality of locations; selecting a destination route from (1) the at least one fleet delivery route and (2) one or more third-party delivery routes; evaluati