Abstract: In one example, a device to calculate a relative set of weighted indices for a set of objectives includes an input device that receives a prioritized list of the set of objectives. A user interface module creates a square matrix of the set of objectives and their subjective relative intensity of importance includes a module to query for subjective intensity of importance between respective objectives in the prioritized list of objectives. The user interface module only presents as options select subjective intensity of importance which preserve a transitivity property of the prioritized list of objectives. A compute module calculates a principle eigenvector of the square matrix to thereby create the relative set of weighted indices.

Abstract: An example method for selecting a task from a plurality of tasks is provided in accordance with an aspect of the present disclosure. The method includes transforming a probabilistic outcome of each task from a predetermined group of tasks to a reference outcome by replacing a probability distribution over values for each of a plurality of dimensions associated with the outcome of a task with a calculated value. The method also includes determining a subgroup of tasks from the predetermined group of tasks based on a comparison of the calculated values, using the calculated values to calculate a utility level for each of the tasks in the subgroup, and selecting a task among the subgroup of tasks.

Abstract: An example method for allocating resources among tasks is provided. The method includes defining each task from a group of tasks in relation to an outcome of the each task. The outcome of each task is associated with a plurality of dimensions with respect to which the outcome is evaluated. The method also includes determining a subgroup of tasks from the group of tasks based on the dimensions associated with the outcomes of the tasks and determining a utility level for each of the tasks in the subgroup by using a utility function. The method further includes identifying a solution for allocating the resources among the subgroup of tasks based on a comparison of the utility level of the tasks.

Abstract: Examples relate to optimizing a portfolio of projects. The examples disclosed herein enable triggering a display of a first graphical representation that may illustrate costs for executing a first portfolio of projects over a time period. The first portfolio may include a set of projects that is selected and scheduled based on a mathematical optimization model. The examples further enable triggering a display of a second graphical representation that may illustrate how the set of projects is scheduled over the time period. The first graphical representation and the second graphical representation may be aligned to a common timeline.

Abstract: A report indicating a user-reported probability of a successful outcome is received. A behavior and information model is estimated based on the report. The behavior and information model includes a behavior model component having a bias parameter and a consistency parameter. The behavior and information model includes an information model component having a first user-believed probability of a successful outcome and a second user-believed probability of a successful outcome. The behavior and information model is used to yield a model-determined probability of a successful outcome that more accurately reflects a probability of a successful outcome than the user-reported probability of a successful outcome does.

Abstract: Methods, systems, and computer-readable and executable instructions are provided for resource planning. Resource planning can include identifying a resource capacity for a given resource planning horizon, identifying a resource pool guideline that defines a priority of resources from which to satisfy a full-time equivalent (FTE) resource planning requirement, and performing resource planning by satisfying the FTE requirement based on the resource capacity and the resource pool guideline.

Abstract: A method and system for selection of a task in proportion to a desired distribution. Specifically, in one embodiment, the present invention discloses a method and system for selecting a task associated with a visiting customer to a web site over a communication network. The customer is assigned to a segment of a target customer base that most closely resembles the customer's characteristics. A plurality of tasks is associated with the segment and can be expressed as a distribution of tasks performed. A current distribution of tasks is determined. The task which provides a new distribution that is closest to a desired distribution of the plurality of tasks is selected to be performed. In one embodiment, the task to be performed is the offering of an advertising promotion to the customer over the communication network.

Abstract: A tool receives parameters relating to target enterprise objective of an enterprise, the cost of an enterprise resource associated with the enterprise, and an enterprise resource capacity. The tool calculates an amount of an enterprise resource to be assigned in an enterprise based on the received parameters relating to the target enterprise objective, the enterprise resource cost, and the enterprise resource capacity.

Abstract: Partitioning job requirements for resource planning can include identifying resource capacity and matching scores of a resource pool for a resource planning horizon, partitioning a full-time equivalent (FTE) job requirement into a plurality of positions based on the resource capacity and matching scores of the resource pool for the resource planning horizon using a computing device, and performing resource planning by allocating the resource capacity to the plurality of positions

Abstract: Information may be extracted from a document. A new pattern may be identified in the document. Classification may be performed based on the extracted information.

Abstract: There is provided a computer-implemented method of generating a data forecasts for different levels of an entity. The method includes generating an aggregate forecast for an upper level entity comprised of two or more components. The method also includes determining mean values and a coefficient of variation for a probability distribution corresponding to future expected decomposition rates for each of the two or more components. A probability distribution parameter vector is computed based on the mean values and the coefficient of variation. The expected future decomposition rates for each of the two or more components may be computed based on the probability distribution parameter vector and a sample observation corresponding to previously observed decomposition values of each of the two or more components. Component forecasts corresponding to each of the two or more components may be computed based on the aggregate forecast and the expected future decomposition rates.

Abstract: Techniques for generating optimized surgery schedules are described in various implementations. In one example implementation, a method that implements the techniques includes receiving a plurality of surgery scheduling requests for surgical procedures to be performed at a surgical facility having a plurality of operating rooms. The method also includes identifying resource constraints associated with the surgery scheduling requests, and identifying an optimization goal for the surgical facility, the optimization goal being defined using weighted optimization parameters. The method also includes generating a proposed surgery schedule for the surgical facility that includes sequencing and operating room assignments for each of the surgical procedures to be performed, the proposed surgery schedule satisfying the resource constraints and being optimized based on the optimization goal for the surgical facility.

Abstract: A method for cost entity matching can include constructing a first graph including a number of first entities and a number of second entities, and assigning a number of first cost values to each of a number of first edges connecting one of the number of first entities to one of the number of second entities in the first graph; adding a second graph to the first graph, wherein the second graph includes the number of first entities and the number of second entities, and assigning a second cost value to each of a number of second edges connecting one of the number of first entities in the first graph to the corresponding first entity in the second graph; and, matching each one of the number of second entities to one of the number of first entities based on the number of first cost values and the second cost values.

Abstract: A method and system of workforce related resource planning is disclosed. The method includes receiving workforce related resource data wherein the workforce related resource data includes demand data and supply data, disaggregating the demand data and the supply data and creating a probability distribution of a workforce gap between the demand data and supply data to quantify risk associated with workforce related resource planning.

Abstract: A method includes receiving flight leg data and dispatcher position data for a planning horizon and identifying cycle flight legs and extraordinary flight legs based on the flight leg data. The method includes allocating each cycle flight leg to at least one dispatcher position while minimizing workload deviations between the dispatcher positions. The method includes allocating, after allocating each cycle flight leg, each extraordinary flight leg to at least one dispatcher position while minimizing workload deviations between the dispatcher positions.

Abstract: Methods, apparatus, and computer readable media with executable instructions stored thereon for resource planning using FTEs are provided. Example methods of the present disclosure can include identifying full time equivalent (FTE) requirements of jobs, skills corresponding to the jobs, resources corresponding to the skills, and FTE capacity of resources [572]. Qualified resources are determined, by a computer, with respect to each job based on the corresponding skills of the resources relative to the skills corresponding to the jobs [574]. FTE capacity of qualified resources is allocated, by a computer, to jobs in a manner that maximizes FTE requirements of jobs having resources allocated thereto, such that a qualified resource is allocated to a job at most to the lesser of the FTE requirement of the job or the FTE capacity of the resource [576].

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: A method for cost entity matching can include constructing a first graph including a number of first entities and a number of second entities, and assigning a number of first cost values to each of a number of first edges connecting one of the number of first entities to one of the number of second entities in the first graph; adding a second graph to the first graph, wherein the second graph includes the number of first entities and the number of second entities, and assigning a second cost value to each of a number of second edges connecting one of the number of first entities in the first graph to the corresponding first entity in the second graph; and, matching each one of the number of second entities to one of the number of first entities based on the number of first cost values and the second cost values.

Abstract: A method includes receiving flight leg data and dispatcher position data for a planning horizon and identifying cycle flight legs and extraordinary flight legs based on the flight leg data. The method includes allocating each cycle flight leg to at least one dispatcher position while minimizing workload deviations between the dispatcher positions. The method includes allocating, after allocating each cycle flight leg, each extraordinary flight leg to at least one dispatcher position while minimizing workload deviations between the dispatcher positions.

Abstract: A method of managing product end of life over an end of life horizon includes the step of selecting an objective of either maximizing gross profit or minimizing writeoff costs for a selected plurality of products being discontinued. The products may have parts in common. A subset of all possible combinations of product demand levels is selected. Each combination is associated with a probability. A procurement plan that optimizes the selected objective is generated based on the selected subset of demand levels given a non-zero pre-existing inventory of at least some parts of the selected products.