Abstract
In this work we present the simultaneous scheduling and optimal control of polymerization reactors using a previously proposed MINLP formulation. The problem is then solved in two ways: first by directly using an Outer Approximation technique, and second, by applying a Lagrangean decomposition scheme that allows the independent solution of the scheduling and optimal control problems. However, both subproblems are linked by a set of Lagrangean Multipliers that evolve during an iterative solution process using a subgradient method. During this process the decomposition approach yields an upper bound to the original problem while a lower bound is obtained heuristically based on the solution of the decomposed problem. The methodology is tested on two polymerization processes and compared vs. the solution obtained when the problem is solved directly. In both cases optimal solutions are almost identical while solution times for the larger problem were reduced significantly when using the decomposition approach.
Published Version
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