On Computing and Pricing of Adjustable Robust Chemical Process Designs
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866910026434609152 |
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| author | Schwientek, Jan Teichert, Katrin Schröder, Jan Höller, Johannes Schwartz, Patrick Asprion, Norbert Schäfer, Pascal Wlotzka, Martin Bortz, Michael |
| author_facet | Schwientek, Jan Teichert, Katrin Schröder, Jan Höller, Johannes Schwartz, Patrick Asprion, Norbert Schäfer, Pascal Wlotzka, Martin Bortz, Michael |
| contents | Model-based process simulation can be used to derive designs and operating conditions of chemical processes that optimally balance multiple objectives, such as quality, costs, or environmental impacts. This work focuses on identifying designs that hedge against uncertainties in model parameters to ensure feasibility, taking the possibility to adjust operating conditions into account. An adaptive scheme is proposed to pinpoint the relevant scenarios in a discretized uncertainty space; these scenarios are then fed into a multi-objective adjustable robust optimization framework reducing the computational burden compared to the consideration of all potential scenarios. Furthermore, we propose a method to quantify the cost or price of robustness, i.e., the compromise which has to be made in comparison to the nominal design case in order to hedge against uncertainty. The conceptual findings are illustrated with an industrially relevant case study. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_15318 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On Computing and Pricing of Adjustable Robust Chemical Process Designs Schwientek, Jan Teichert, Katrin Schröder, Jan Höller, Johannes Schwartz, Patrick Asprion, Norbert Schäfer, Pascal Wlotzka, Martin Bortz, Michael Optimization and Control 90C17, 90C29, 90C30, 90C47, 90C90 G.1.6 Model-based process simulation can be used to derive designs and operating conditions of chemical processes that optimally balance multiple objectives, such as quality, costs, or environmental impacts. This work focuses on identifying designs that hedge against uncertainties in model parameters to ensure feasibility, taking the possibility to adjust operating conditions into account. An adaptive scheme is proposed to pinpoint the relevant scenarios in a discretized uncertainty space; these scenarios are then fed into a multi-objective adjustable robust optimization framework reducing the computational burden compared to the consideration of all potential scenarios. Furthermore, we propose a method to quantify the cost or price of robustness, i.e., the compromise which has to be made in comparison to the nominal design case in order to hedge against uncertainty. The conceptual findings are illustrated with an industrially relevant case study. |
| title | On Computing and Pricing of Adjustable Robust Chemical Process Designs |
| topic | Optimization and Control 90C17, 90C29, 90C30, 90C47, 90C90 G.1.6 |
| url | https://arxiv.org/abs/2512.15318 |