Abstract: A method and system are disclosed for managing configurable products via solving an optimization problem. In one embodiment, the method comprises collecting data from a software application and a user; formulating a set of constraints based on the collected data; defining the optimization problem by the set of constraints and an optimization objective; solving the optimization problem using the collected data, the set of constraints, the optimization objective and the objective function via mixed integer programming; and outputting a solution of the optimization problem.

Abstract: A computer-implemented method for resource management includes storing in a memory a set of resource consumers, resources for allocation to the resource consumers, and initial binary constraints applying to the allocation of the resources. Respective variables are associated with the resource consumers, and the resources are identified as values applicable to the variables. A non-binary scoring criterion is applied to generate scores on a graded scale for proposed assignments of one or more of the resources to respective ones of the resource consumers. One or more additional binary constraints are defined based on the graded scale of the scores. An assignment is found of the values to the variables that satisfies the initial and additional binary constraints using a constraint satisfaction problem (CSP) solver running on a processor that is coupled to the memory. The resources are assigned to the resource consumers responsively to the assignment of the values to the variables.

Abstract: A computer-implemented method for resource management includes storing in a memory a set of resource consumers, resources for allocation to the resource consumers, and initial binary constraints applying to the allocation of the resources. Respective variables are associated with the resource consumers, and the resources are identified as values applicable to the variables. A non-binary scoring criterion is applied to generate scores on a graded scale for proposed assignments of one or more of the resources to respective ones of the resource consumers. One or more additional binary constraints are defined based on the graded scale of the scores. An assignment is found of the values to the variables that satisfies the initial and additional binary constraints using a constraint satisfaction problem (CSP) solver running on a processor that is coupled to the memory. The resources are assigned to the resource consumers responsively to the assignment of the values to the variables.

Abstract: The substitution of employees in a service engagement is a computer based method designed to consider a set of attributes that describe the resource capabilities required for delivering a services engagement and identify the actual real-world human assets that can be substituted and/or matched to these attributes. The method will produce an allocation plan that provides the set of permissible substitutes for a given resource demand, given a set of allowable substitute resources for a particular resource attribute, and substitution and matching rules for the given resource demand. A set of metrics is created that identify which substitutions are best relative to the ideal match of resources to the demand.

Abstract: A system and method are disclosed for allocating human resources to tasks using constraint satisfaction programming, where fictitious persons are used to satisfy required constraints, to ensure that the solution process continues until a solution is found, and capability constraints and job constraints are relaxed until a solution is found. Tasks using fictitious persons are identified, and information about task capability requirements not met and capabilities of unallocated human resources are displayed so that constraints may be relaxed and fictitious persons removed. There is provision for handling multi-task jobs where if a fictitious person is assigned to any task then all tasks will be assigned a fictitious person.

Abstract: The invention provides a method for optimizing a sourcing strategy for potential services offerings of large, multinational services organizations. This optimization method considers existing capabilities, resource skills, locations of the resources, costs of the resources, desired profit margins and other strategic sourcing policies to produce an optimized service offering staffing plan.