Optimization problems in chemical process design involve a significant number of discrete and continuous decisions. When taking into account uncertainties, the search space is very difficult to explore, even for experienced engineers. Moreover, it should be taken into account that while some decisions are fixed at the design stage, other parameters can be adapted to the realization of the uncertainty during the operation of the plant. This leads to a two-stage optimization problem which is difficult to solve. To address this challenge, we propose to combine commercial process simulation software with an evolutionary strategy. This approach is applied to designing a downstream process to isolate valuable products from pyrolysis oil produced by the catalytic pyrolysis of rigid polyurethane foam. The suggested algorithm consistently performed better than a manually designed robust process. Additionally, the analysis of different scenarios provided insight into promising changes in the overall layout of the recycling process.

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