This US-Argentina Cooperative Science award will support the collaboration of Ignacio Grossmann of Carnegie Mellon University and Jaime Cerda of the Universidad Nacional del Litoral (UNL), Argentina. The project aims to develop new algorithmic methodologies for production planning and scheduling of multipurpose batch plants producing simultaneously products of low to medium demand. A goal of these methodologies will be to satisfy product demands on time, but also minimize idle times and product inventories. Another objective will be to develop realistic models that account for assignments of groups of consecutive tasks to a single equipment item, simultaneous production of intermediate and finished products, multiple processing paths, and setup/changeover times. To develop effective solution methods, models will be investigated that do not rely on discretization of the time domain, and that can be enhanced with fast heuristic techniques. The proposed techniques will be implemented within an expert system shell that can provide for better insights and understanding by the user. This project is expected to produce benefits to both sides that will complement existing research in optimization and batch processing at Carnegie Mellon and UNL.
