Abstract: Systems, methods, and computer-readable and executable instructions are provided for selecting data paths. Selecting data paths can include creating a support data tree structure from a number of data trees within a data set. In addition, selecting data paths can include removing a number of paths from the support data tree based on a number of evaluations of each of a number of nodes within the support data tree. Furthermore, selecting data paths can include selecting a desired set of paths based on a desired number of removed paths and an associated number of evaluations of the support data tree.

Abstract: A method for optimizing allocations in a workforce allocation plan begins when resource data is received. The resource data includes data that relates to employee resources and to demand for the employee resources. A first set of employee resource pairings is established using the user's resource preferences to assigning the employee resources to the demand for the employee resources. A second set of employee resource pairings is established using predetermined resource preferences to assign the employee resources to the demand for the employee resources. The second set of employee resource pairings includes all employee resource pairings that belong to an optimal solution. The first and second sets of employee resource pairings are compared to provide the workforce allocation plan having the optimal solution with the maximum number of the user's resource preferences to optimize allocations in the workforce allocation plan.

Abstract: Example embodiments disclosed herein relate to a mechanism for optimizing a resource matching model. In particular, a mechanism is provided to access, in a resource matching system, input data for a mixed integer programming (MIP) model, which may include resource data describing resources and demand data describing corresponding demand instances. Mechanisms are also provided to convert the MIP model to a binary integer programming (BIP) model by redefining the input data to unary data and to map the BIP model to a bipartite graph using the unary data. The resulting bipartite graph may include a number of nodes including a first set corresponding to the resources and a second set corresponding to the demand instances, and a number of edges corresponding to decision variables of the BIP model, each edge representing a potential allocation of a resource in the first set to a demand instance in the second set.