Abstract: A neuromodulation therapy is delivered via at least one electrode implanted subcutaneously and superficially to a fascia layer superficial to a nerve of a patient. In one example, an implantable medical device is deployed along a superficial surface of a deep fascia tissue layer superficial to a nerve of a patient. Electrical stimulation energy is delivered to the nerve through the deep fascia tissue layer via implantable medical device electrodes.

Abstract: A neuromodulation therapy is delivered via at least one electrode implanted subcutaneously and superficially to a fascia layer superficial to a nerve of a patient. In one example, an implantable medical device is deployed along a superficial surface of a deep fascia tissue layer superficial to a nerve of a patient. Electrical stimulation energy is delivered to the nerve through the deep fascia tissue layer via implantable medical device electrodes.

Abstract: In one aspect, a computer-implemented method is provided for aggregating and scheduling product batches in a manufacturing environment. Using a batch aggregation engine implementing a mathematical programming strategy, one or more product demands are allocated to one or more product batches having suggested sizes and suggested starting times. The mathematical programming strategy includes evaluating a number of time-based penalties relative to one another in allocating the demands to the batches, the time-based penalties being based on relationships between suggested starting times for batches and times of demands being considered for allocation to batches. The suggested sizes, the suggested starting times, and feedback relating to the suggested sizes and suggested starting times are communicated from the batch aggregation engine to a scheduling engine to assist the scheduling engine in scheduling starting times for the batches.

Abstract: In one aspect, a computer-implemented method is provided for aggregating and scheduling product batches in a manufacturing environment. Using a batch aggregation engine implementing a mathematical programming strategy, one or more product demands are allocated to one or more product batches having suggested sizes and suggested starting times. The mathematical programming strategy includes evaluating a number of time-based penalties relative to one another in allocating the demands to the batches, the time-based penalties being based on relationships between suggested starting times for batches and times of demands being considered for allocation to batches. The suggested sizes, the suggested starting times, and feedback relating to the suggested sizes and suggested starting times are communicated from the batch aggregation engine to a scheduling engine to assist the scheduling engine in scheduling starting times for the batches.

Abstract: In one aspect, a computer-implemented method is provided for aggregating and scheduling product batches in a manufacturing environment. Using a batch aggregation engine implementing a mathematical programming strategy, one or more product demands are allocated to one or more product batches having suggested sizes and suggested starting times. The mathematical programming strategy includes evaluating a number of time-based penalties relative to one another in allocating the demands to the batches, the time-based penalties being based on relationships between suggested starting times for batches and times of demands being considered for allocation to batches. The suggested sizes, the suggested starting times, and feedback relating to the suggested sizes and suggested starting times are communicated from the batch aggregation engine to a scheduling engine to assist the scheduling engine in scheduling starting times for the batches.

Abstract: In one embodiment, a method is provided for collaboratively solving an optimization problem using at least first optimization software and second optimization software each having at least partial information concerning the optimization problem.

Abstract: In one embodiment, a method is provided for collaboratively solving an optimization problem using at least first optimization software and second optimization software each having at least partial information concerning the optimization problem.

Abstract: A computer-based system (10) for aggregating and scheduling product batches (50) includes a batch aggregation engine (20) that allocates one or more product demands (40) to one or more product batches (50) having suggested sizes and suggested starting times. The batch aggregation engine (20) communicates to a scheduling engine (30) the suggested batch sizes, the suggested starting times, and feedback (26) relating to the suggested sizes and suggested starting times to assist the scheduling engine (30) in scheduling a start time for each product batch (50). The system (10) may also include a scheduling engine (30) coupled to the batch aggregation engine (20) that receives the suggested sizes, suggested starting times, and feedback (26) from the batch aggregation engine (20). The scheduling engine (30) schedules a starting time for one or more of the batches (50) according to the suggested sizes, suggested starting times, and feedback (26) received from the batch aggregation engine (20).

Abstract: A computer-implemented system (10) for task scheduling. The system (10) models an enterprise in terms of products, tasks and resources used to make them, and constraints imposed in scheduling tasks. A scheduling engine, comprised of a genetic algorithm (13) and a schedule builder (14), operates on the model to produce candidate schedules. The schedule builder (14) uses graph theory techniques to solve tightly constrained scheduling problems. Each candidate schedule is evaluated and used to generate an improved schedule in accordance with genetic processing, until a best schedule is produced.