Abstract: A system 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: determining that a respective number of totes for a respective order of one or more orders can be reduced; reducing, using an infeasible totes loop, the respective number of the totes for the respective order to a respective reduced number of the totes; executing, as part of the infeasible totes loop, an item search; running the item search until a predefined number of iterations is reached; generating directions for a route of a pick walk based on a map of a retail facility; and facilitating displaying, on an electronic device, the route of the pick walk on the map of the retail facility. Other embodiments are disclosed herein.

Abstract: A system 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, perform certain acts. The acts can include obtaining an original load design for loading a trailer to deliver stacks of pallets to physical stores. The load design specifies a respective floor spot assignment for each of the stacks. The original load design satisfies center-of-gravity constraints. The acts also can include generating fluid groups of the stacks to form an initial fluid grouping. The acts additionally can include determining that the fluid groups do not collectively satisfy the center-of-gravity constraints. The acts further can include until the fluid groups collectively satisfy the center-of-gravity constraints, repeatedly determining one or more infeasible groups from the fluid groups, and adjusting at least one of the one or more infeasible groups to update the fluid groups.

Abstract: A method including obtaining information about a trailer that has been partially loaded with preloaded stacks in a manner that deviates from an original load design. The trailer is loaded with stacks of pallets including (i) the preloaded stacks that have already been loaded in the trailer and (ii) unloaded stacks that have not yet been loaded into the trailer. The method also can include determining positions of empty floor spots remaining in the trailer. The method additionally can include determining a first portion of an incremental load design for the unloaded stacks using a gap-filling pattern behind an uneven rear edge of the preloaded stacks in the trailer. The method further can include determining a second portion of the incremental load design.

Abstract: This application relates to automated processes for assigning item containers, such as boxes, to a location on a shipping container, such as a pallet. For example, a computing device may receive an item assignment request identifying a plurality of item containers, and determines a subset of the plurality of item containers for assigning to a layer of a shipping container. Further, the computing device determines a plurality of positions and a plurality of orientations for each of the subset of the plurality of item containers. The computing device also assigns the subset of the plurality of item containers to the layer of the shipping container based on the plurality of positions and the plurality of orientations. The computing device further generates an item assignment response identifying the assignments of the plurality of item containers, and transits the item assignment response for display.

Abstract: This application relates to automated processes for assigning item containers, such as boxes, to a location on a shipping container, such as a pallet. For example, a computing device may receive an item assignment request identifying a plurality of item containers, and determines a subset of the plurality of item containers for assigning to a layer of a shipping container. Further, the computing device determines a plurality of positions and a plurality of orientations for each of the subset of the plurality of item containers. The computing device also assigns the subset of the plurality of item containers to the layer of the shipping container based on the plurality of positions and the plurality of orientations. The computing device further generates an item assignment response identifying the assignments of the plurality of item containers, and transits the item assignment response for display.

Abstract: In some examples, a system may include a first computing device communicatively coupled to a second computing device. Additionally, the first computing device is configured to obtain, from the second computing device, check-in data indicating an arrival of the user of the second computing device at a first location, and in response to obtaining the check-in data, determine current wait times. Moreover, the first computing device is configured to determine a first number of customers waiting for service, determine a first number of associates available to assist the first number of customers, and determine an expected wait time for the user operating the second computing device based at least on the current wait times. In some examples, the first number of customers waiting for service, and the first number of associates available. Further, the first computing device is configured to transmit the expected wait time to the second computing device.

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 computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform certain acts. The acts can include determining an estimated arrival time of a user at a physical store. The acts also can include generating an estimated wait time using a machine learning model and based on input data comprising the estimated arrival time and dynamic wait time data for the physical store. The acts additionally can include sending the estimated wait time to at least one of the physical store or a mobile device of the user. Other embodiments are disclosed.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform certain acts. The acts can include obtaining a route for delivering one or more orders in a tri-temp trailer from a distribution center to physical stores in a sequence of stops. The route can have an associated assignment of stack groups comprising stacks of pallets. The acts also can include determining a load design for the stacks in the tri-temp trailer based on the sequence of the stops in the route, such that unloading each of the stacks is minimized when the tri-temp trailer delivers the orders to the physical stores. The acts additionally can include outputting the load design to cause the stacks to be loaded in the tri-temp trailer according to the load design for delivery to the physical stores in the sequence of stops. The load design can specify a respective floor spot assignment for each of the stacks.

Abstract: A system for generating a geographically-clustered routing solution includes a computer system configured to receive a plurality of orders. Each order in the plurality of orders comprises a geographic location. The plurality of orders are clustered into a plurality of clusters based on the geographic location of each order and a routing solution is generated for each of the plurality of clusters. Each routing solution is transmitted to at least one vehicle system.

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 respective number of totes for each respective order of one or more orders; determining, using a first set of rules, when the respective number of totes for a respective order of the one or more orders can be reduced; when the respective number of totes is determined to be able to be reduced, reducing, using a second set of rules, the respective number of totes for the respective order to a respective reduced number of totes for the respective order of the one or more orders; comparing the respective number of totes for the respective order to the respective reduced number of totes for the respective order; and when the respective number of totes for the respective order is compared to be equal to the respective reduced number of totes for the respective order, facilitating displaying, on an electronic device

Abstract: A system comprising 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 operations comprising: generating a schedule summary comprising one or more selectable portions of availability for drivers; receiving a selection of an unfilled portion of a respective schedule for a respective driver of the drivers adds the respective driver to a list of respective drivers to be scheduled on the schedule summary displayed on a GUI of an electronic device of a user; receiving one or more selections of the one or more selectable portions of availability of the schedule summary causes one or more changes to occur on the schedule summary displayed on the GUI of the electronic device of the user; and displaying one or more schedules for the drivers. Other embodiments are disclosed herein.

Abstract: A system 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, perform certain acts. The acts can include obtaining information about a trailer that has been partially loaded with preloaded stacks in a manner that deviates from an original load design. The trailer is being loaded with stacks of pallets comprising the preloaded stacks and unloaded stacks. The acts also can include determining positions of empty floor spots remaining in the trailer. The acts additionally can include determining a first portion of an incremental load design for the unloaded stacks using a gap-filling pattern behind an uneven rear edge of the preloaded stacks. The acts further can include determining a second portion of the incremental load design. The acts additionally can include updating the incremental load design based on an overall load design of the trailer.

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 cause the one or more processors to perform (1) receiving one or more first delivery routes comprising one or more delivery stops in a sequence; (2) shuffling the one or more delivery stops among the one or more first delivery routes to create one or more second delivery routes different than the one or more first delivery routes; (3) determining whether the one or more second delivery routes are on a list of banned delivery routes; (4) when (a) the one or more second delivery routes are not on the list of banned delivery routes and (b) a second cost of the one or more second delivery routes is lower than a first cost of the one or more first delivery routes, persisting the one or more second delivery routes in the one or more non-transitory computer-readable storage devices; and (5) repeating (2) through (4) until the second cos

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 to generate one or more schedules for one or more drivers; determining one or more respective day cab schedules for each respective day cab driver of the one or more drivers; assigning one or more permanent drivers of the one or more drivers to one or more permanent tractors; assigning at least one driver of one or more remaining drivers of the one or more drivers to at least one tractor using a first set of rules; generating the one or more schedules for the one or more drivers; and coordinating displaying the one or more schedules for the one or more drivers on an electronic device of a user. Other embodiments are disclosed herein.

Abstract: A system 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: receiving multiple purchase orders for delivery of items from vendors to distribution centers of a distribution network over a period of time, wherein each of the multiple purchase orders specifies a respective vendor of the vendors and a respective distribution center of the distribution centers; generating partitions of the distribution network; generating respective candidate load routes for fulfilling the purchase orders for each of the partitions in parallel using a multi-threaded column generation engine; and selecting final load routes from the respective candidate load routes. Other embodiments are disclosed.

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 cause the one or more processors to perform receiving one or more orders comprising a list of one or more pallets; grouping each pallet of the one or more pallets into one or more groups using one or more respective qualities of each respective pallet; for each group of the one or more groups, building one or more stacks of pallets using at least three different stacking models; selecting a final stack list of a model of the at least three different stacking models having a lowest number of stacks; and optimizing the final stack list using a probabilistic model. Other 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 acts of (1) receiving one or more orders; (2) inserting the one or more orders into a plurality of pre-constructed routes to create a plurality of modified routes; (3) selecting a route of the plurality of modified routes with a lowest cost; (4) generating an initial load plan for the route with the lowest cost; (5) when the initial load plan does not pass one or more feasibility checks, splitting the one or more orders into two or more orders; and (6) repeating (1) through (5) until no more orders remain. Other embodiments are disclosed herein.

Abstract: A method to be implemented via execution of computing instructions configured to run at one or more processors and stored at one or more non-transitory computer-readable media. The method can include determining, via a source-departure-prediction machine learning model, a source departure time for a delivery route to one or more stops based at least in part on a load ready time. The source-departure-prediction machine learning model can include a first model and a second model. Determining the source departure time further can include using the first model to determine the source departure time, while not using the second model, when a commodity type of the delivery route is of a first type; and using the second model to determine the source departure time, while not using the first model, when the commodity type of the delivery route is not of the first type. The method additionally can include determining a respective transit time for each of one or more legs for the delivery route.