Infeasible Path Global Flowsheet Optimization Using McCormick Relaxations

摘要

Deterministic global methods for flowsheet optimization have almost exclusively relied on equation-oriented formulations. The automatic propagation of McCormick relaxations and subgradients enables an alternative formulation similar to sequential modular infeasible path methods in local optimization that operate in a reduced space while moving most model variables and equations to external functions. The application of this reduced-space formulation is demonstrated for the Williams-Otto process. For suitable choices of tear streams and additional variables and equations left to the optimizer, it enables significant reductions in computational time compared to equation-oriented formulations.