Abstract: Embodiments of the present invention provide a method, system and computer program product for an integrated business rules management system (BRMS) and mixed integer programming (MIP) technology application deployment. In an embodiment of the invention, a method of rules processing with MIP constraints can include selecting candidate rules from amongst a set of rules in a rules engine executing in memory of a computer and reducing the candidate rules to rules in a conflict set according to constraints specified in the candidate rules. The method also can include conflict resolving the rules in the conflict set and generating an agenda for the rules of the conflict set. Finally, the method can include adding constraints specified in the rules of the conflict set to working memory of the rules engine and applying the rules in the conflict set in agenda order to the working memory.

Abstract: Embodiments of the present invention provide a method, system and computer program product for an integrated business rules management system (BRMS) and mixed integer programming (MIP) technology application deployment. In an embodiment of the invention, a method of rules processing with MIP constraints can include selecting candidate rules from amongst a set of rules in a rules engine executing in memory of a computer and reducing the candidate rules to rules in a conflict set according to constraints specified in the candidate rules. The method also can include conflict resolving the rules in the conflict set and generating an agenda for the rules of the conflict set. Finally, the method can include adding constraints specified in the rules of the conflict set to working memory of the rules engine and applying the rules in the conflict set in agenda order to the working memory.

Abstract: The method provides a planning system where production plans and safety stocks are determined simultaneously, thus resulting in coupled target stock calculation and production plan. The closer the manufacturing process gets to the next production event, the lower the safety stock needs to be. In this approach, assumptions on the average production lead time—which might be wrong—do not need to be made. Indeed, if the production plan and the safety stock are simultaneously computed, it is clear when the next production is going to occur. As a result, production variability only needs to be considered in relation to the probability of unexpected events in manufacturing (e.g. a machine breakdown) as opposed to taking provision for variability of the production cycle due to situations that can be anticipated at the planning step.

Abstract: The method provides a planning system where production plans and safety stocks are determined simultaneously, thus resulting in coupled target stock calculation and production plan. The closer the manufacturing process gets to the next production event, the lower the safety stock needs to be. In this approach, assumptions on the average production lead time—which might be wrong—do not need to be made. Indeed, if the production plan and the safety stock are simultaneously computed, it is clear when the next production is going to occur. As a result, production variability only needs to be considered in relation to the probability of unexpected events in manufacturing (e.g. a machine breakdown) as opposed to taking provision for variability of the production cycle due to situations that can be anticipated at the planning step.