An efficient and user-friendly optimization framework for batch process scheduling

Abstract

This contribution reports on an optimization framework for the formulation and the solution of batch scheduling problems. The problems are graphically modeled as extended resource task networks (eRTN). The extended resource task networks are automatically translated to timed automata (TA) and are composed by parallel composition to form a global automaton that represents the complete scheduling problem. An efficient cost-optimal reachability analysis is performed on the global automaton to derive the schedules. The schedules are presented graphically as Gantt-charts to the user and can be revised when required. The main advantage of this approach over standard mathematical programming techniques is the intuitive graphical and modular modeling and the ability to compute solutions within reasonable periods of time. The proposed framework is tested on a scheduling problem in a pipeless plant to demonstrate a successful application.