Pareto‐Optimal Treatment of Uncertainties in Model‐Based Process Design and Operation

It is described how to handle here-and-now (i.e., process design-related) and wait-and-see (i.e., process operation-related) decisions in a multicriteria framework. This approach exploits the adjustability for the wait-and-see variables while at the same time respecting optimality guarantees on process key performance indicators.

Abstract

Model-based process design and operation involves here-and-now and wait-and-see decisions. Here-and-now decisions include design variables like the size of heat exchangers or the height of distillation columns, whereas wait-and-see decisions are directed towards operational variables like reflux and split ratios. In this contribution, we describe how to deal with these different types of decisions in a multicriteria framework, offering an adjustability for the wait-and-see variables while at the same time respecting optimality guarantees on process key performance indicators (KPIs).

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