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: determining one or more work orders for a service provider; determining an optimal service route for the one or more work orders; updating an available time slot in a work schedule of the service provider; and transmitting the work schedule updated with the optimal service route to be displayed on a user interface executed on a device of the service provider. Other embodiments are also provided.

An exemplary embodiment of the present application is a system and method for work allocation optimization. In the present disclosure, analytics are applied to work items while the work items are waiting in a work queue in order to optimize the routing and allocation of work items to agents in the most efficient manner possible, while optimizing the utilization of agents. By performing a look ahead at more than the initial work item, the system assesses the agent skills required by imminent work items in the work queue. This is then compared to a skillset of each available and/or soon to be available agent in order to achieve the optimal allocation of the work items to maximize utilization of agents. The work items are then routed to the agents accordingly.

An embodiment includes parsing form data into a plurality of form values received with a schedule request and assembling the form values into a search vector. The embodiment searches historical data using a nearest neighbor algorithm that inputs the search vector and identifies first and second sets of historical vectors comprising that are closest by Euclidean distance to the search vector. The embodiment calculates an enhanced constraint vector comprising an average value based at least in part on the first set of historical vectors and a standard deviation value based at least in part on the second set of historical vectors. The embodiment generates an employee schedule using an optimization algorithm subject to a plurality of schedule constraints that include the enhanced constraint vector. The embodiment then transmit data for initiating a notification regarding availability of the employee schedule.

Facilitating striated random restart during routing of resources using a heuristic approach is provided herein. Operations of a system can include, separating objects of a group of objects into a first grouping and a second grouping, assigning first objects of the first grouping and second objects of the second grouping to respective resource elements, resulting in a first classification. A search space is enabled and includes, at respective iterations of a group of iterations, selecting a defined priority level, removing third objects of the second grouping that do not satisfy the defined priority level from the first classification, and assigning the third objects to the respective resource elements, resulting in a second classification. The first objects and the second objects, other than the third objects, remain assigned according to the first classification. According to an implementation, the schedule search reduces a search space of the group of objects.

A computer-implemented method for implementing a map calendar application and corresponding map calendar GUI that provide time mold functionality is described herein. The method includes executing the map calendar application to provide the map calendar GUI surfaced on a display. The map calendar GUI includes an interactive visualization of a map calendar, which includes a continuous, manipulable sequence of calendar content data corresponding to calendar content items that are organized based on units of time within a coordinate plane. The method also includes categorizing the calendar content items based on time categories corresponding to the calendar content items and identifying time patterns corresponding to the categorized calendar content items. The method further includes generating a time mold of the map calendar based on the identified time patterns and visually overlaying the time mold onto corresponding calendar content items within the interactive visualization.

A crew planning system includes a demand forecasting module and an optimization module. The system forecasts anticipated reserve demand levels, and determines suitable reserve staffing approaches to meet anticipated reserve demand. The forecasting is based upon probabilistic distribution models which take into account variability associated with reserve demand for a particular day. Via use of the crew planning system, reserve staffing expenses may be reduced and/or reserve demand may be met with a higher degree of probability.

A computer-implemented method of training machine learning models for making simulated estimations is provided. The method includes collecting, from a database, a set of historical data, applying one or more transformations to the set of historical data to create a set of model features, and separating the set of model features into one or more pools, each pool comprising one or more model features of the set that are homogeneous with respect to a common value. the method further includes, for each pool, dynamically creating a training set that includes the one or more sets of model features of the pool and at least some of the historical data. The method further includes, for each training set, training a machine learning model on the training set.

Described herein is a computer implemented method. The method comprises receiving, from a server application, project data defining a plurality of tasks and a plurality of iterations, each iteration having a start time and an end time and displaying, on a display, a timeline graphical user interface including a plurality of task timelines, each task timeline corresponding to one of the plurality of tasks. The method further comprises detecting a first user input, the first user input associated with a particular task and, in response to detecting the first user input, displaying a plurality of available drop zones in the particular task's timeline, each available drop zone corresponding to an available iteration, an available iteration being an iteration that the particular task can be assigned to.

According to some embodiments, disclosed are systems and methods for dynamic optimized activity-assignment processing based on a periodic assessment of user fatigue risk via wearable devices. The disclosed technology receives tracking data related to movements and activities of a plurality of users working at a location and determines a user-specific injury prone score for each user. Based on this, the technology analyzes a current activity assignment schedule, which is modified to correspond to the current capabilities of each user at the location. As a result, a notification is generated and communicated to each user so as to alert them to their new assignment.

A method and system remotely controlling a cleaning cycle of a household appliance using transmission of wireless signals is provided. Signals are transmitted between a mobile dispensing device arranged in the household appliance and an electronic device. The method determines the strength of a signal received by the mobile dispensing device. The determined strength is compared to a threshold value. If the determined strength is above the threshold value transmission of wireless signals from the mobile dispensing device to the electronic device is enabled. If the determined strength is below the threshold value transmission of signals from the mobile dispensing device to the electronic device is disabled. When transmission of signals is enabled, a status wireless signal comprising status information about the cleaning cycle is sent to the electronic device.