A case study of multi-objective optimization under uncertainty in process design for sustainability

In order to design a sustainable chemical process, its economic, environmental
and societal objectives need to be achieved simultaneously. This can be formulated as a multi-objective optimization (M-OO) problem. A chemical process comes across various uncertainties throughout process design and operation in the form of manufacturing variations, material property variations, market fluctuation, etc. Hence, M-OO under uncertainty techniques need to be deployed to search the optimal strategy for sustainability enhancement.
Gani’s group developed a methodology for systematic generation and
evaluation of alternatives in the design of sustainable processes. This work attempts to extend the prior research in this field by introducing M-OO under uncertainty in process design for sustainability. A multi-step optimization approach is utilized to achieve the final decision. The effectiveness of this methodology is demonstrated by means of a case study.