Robust optimization for engineering design

This study proposes a robust optimization model to handle uncertainty during the process design stage, together with a decision-making procedure. Different robustness concepts are presented to describe the characteristic, either economic or technical, of a given variable in the model. Among economic robustness measures, partial mean of costs is analysed to address its intrinsic problem of excessive variability of performance with respect to the change of values in its parameters. To resolve it, a novel formulation of robust economic optimization is derived, providing a conceptual framework for suggesting a proper range of parameter values. Then, the model is further extended to consider technical robustness as well. Lastly, the decision-making procedure is presented using the proposed nadir vector which is computationally inexpensive and also useful in selecting a final solution. The applicability of the model was successfully demonstrated by applying it to process design examples.

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