Abstract: Systematically and comprehensively identifying and evaluating structure changes in MRP runs.

Abstract: Systematically and comprehensively identifying and evaluating structure changes in MRP runs.

Abstract: Methods and systems for identifying stability exceptions in a data log are disclosed. In one method, at least one key that is present in the data log is determined. The data log is comprised of at least one data set, at least one of which includes a plurality of iterations indicating states of the corresponding data set at different points in time. For each data set and for each key, a map is generated. The map indicates, for each iteration of the corresponding data set, whether the corresponding key is present in the corresponding iteration. Moreover, at least one expression pattern rule that models data item stability characteristics over data set iterations is compared to each of the maps to determine whether the corresponding map satisfies the one or more expression pattern rules. Further, at least one unstable data item is identified in the data log based on the comparison.

Abstract: Methods and systems for identifying stability exceptions in a data log are disclosed. In one method, at least one key that is present in the data log is determined. The data log is comprised of at least one data set, at least one of which includes a plurality of iterations indicating states of the corresponding data set at different points in time. For each data set and for each key, a map is generated. The map indicates, for each iteration of the corresponding data set, whether the corresponding key is present in the corresponding iteration. Moreover, at least one expression pattern rule that models data item stability characteristics over data set iterations is compared to each of the maps to determine whether the corresponding map satisfies the one or more expression pattern rules. Further, at least one unstable data item is identified in the data log based on the comparison.

Abstract: A method is disclosed in one embodiment of the invention as including receiving standard MRP input data, including supply rules. Demand priority data may also be received to provide a business ranking of the independent demands. The MRP input data and demand priority data may be transformed into a format usable by an implosion engine and a pegging solver. Such transformation may include providing artificial MRP input data for each of the components. The transformed MRP input data may be processed with the implosion engine and the pegging solver to provide pegged implosion data. A pegged supply shortfall for a component may then be calculated based on the pegged implosion data. Specifically, consumption of an artificial component may represent a supply shortfall for the component. The demand priority data for the independent demand that pegs to the supply shortfall may provide the prioritized shortfall for that component.

Abstract: A distributed, network-based system and computer program product determines an optimal allocation of available to promise components in a supply chain. An aggregate demand request is generated by a demand entity intelligent agent. The aggregate demand request is propagated via a network throughout the supply chain to a plurality of supply entity intelligent agents. The supply entity intelligent agents respond with an evaluation of available to promise supply capability. Optimal allocation of the available to promise supply is made by calculating a sequence of squared set solutions of unit demand problems using a message-based communications protocol between the demand entity and supply entity intelligent agents.

Abstract: A distributed, network-based system and computer program product determines an optimal allocation of available to promise components in a supply chain. An aggregate demand request is generated by a demand entity intelligent agent. The aggregate demand request is propagated via a network throughout the supply chain to a plurality of supply entity intelligent agents. The supply entity intelligent agents respond with an evaluation of available to promise supply capability. Optimal allocation of the available to promise supply is made by calculating a sequence of squared set solutions of unit demand problems using a message-based communications protocol between the demand entity and supply entity intelligent agents.

Abstract: A distributed, network-based system, method, and computer program product determines an optimal allocation of available to promise components in a supply chain. An aggregate demand request is generated by a demand entity intelligent agent. The aggregate demand request is propagated via a network throughout the supply chain to a plurality of supply entity intelligent agents. The supply entity intelligent agents respond with an evaluation of available to promise supply capability. Optimal allocation of the available to promise supply is made by calculating a sequence of squared set solutions of unit demand problems using a message-based communications protocol between the demand entity and supply entity intelligent agent.

Abstract: A distributed, network-based system, method, and computer program product determines an optimal allocation of available to promise components in a supply chain. An aggregate demand request is generated by a demand entity intelligent agent. The aggregate demand request is propagated via a network throughout the supply chain to a plurality of supply entity intelligent agents. The supply entity intelligent agents respond with an evaluation of available to promise supply capability. Optimal allocation of the available to promise supply is made by calculating a sequence of squared set solutions of unit demand problems using a message-based communications protocol between the demand entity and supply entity intelligent agent.