DMI-9561853 Miller This Small Business Innovation Research (SBIR) Phase I develops new software for solving planning, and scheduling problems in flexible manufacturing facilities. The software design is directed to solutions for large-scale industrial planning and scheduling. benefits are expected in increased production capacity, reduced waste, lower operating costs, reduced inventories, and shorter response time to customer orders. The approach is a rigorous mathematical formulation of planning and scheduling problems and relies on a novel problem decomposition methodology. The decomposition scheme uses a sliding time window containing a detailed model, coupled to a coarse-grained planning model for the remainder of the time horizon. The heart of the method is an automated mechanism for propagating a detailed window along the time axis in an iterative fashion, much like numerical integration. The time axis is decomposed into fine and coarse grained sections. In the fine grained section, the scheduling problem will be modeled and solved as a mixed-integer linear program. The length of the fine-grained time window is chosen so that the scheduling subproblem may be solved using a customized algorythm. The remainder of the time horizon (outside the fine grained window) will be modeled using aggregate constraints and solved by relaxing integrality conditions. This allows such macroscopic features as plant capacity and anticipated product demand to be propagated into each detailed scheduling subproblem. If successful, this research will provide a new engine for scheduling tools useful in process industries. Available software is difficult and expensive to install and maintain and does not provide high quality solutions. The new software is expected to reduce customization and installation time and yet provide high quality results.
