Production campaign planning including grade transition sequencing and dynamic optimization

A method is presented for solving a production optimization problem consisting of the determination of transition trajectories, operating points, and sequencing for manufacturing a set of products. The complete production problem is split up into a dynamic optimization problem (primal problem), and a mixed-integer linear problem (master problem), which is related to the sequencing/scheduling. Information for construction of the master problem is obtained from the solutions of the primal problems. The complete problem is solved through an iterative procedure. The method is a modular and application-specific alternative to standard methods such as Benders Decomposition and Outer Approximation, and offers advantages in comparison to these. The modularity of the approach provides for flexibility in choosing the optimization tools. The method is illustrated by determining optimal production campaigns for a polymerization process.