Decision-Making for Sustainability Enhancement of Chemical Systems under Uncertainties: Combining the Vector-Based Multiattribute Decision-Making Method with Weighted Multiobjective Optimization Technique

The identification of the best solution for improving the sustainability of chemical systems is quite challenging because multiple objectives have to be considered and the trade-offs among the objectives must be addressed. This study aims to develop a novel framework to simplify multiobjective optimization (MOO) problems by incorporating a vector-based multiattribute decision-making (MADM) method. In the framework, the enhancement system is first defined and characterized on a case-by-case basis in the first phase, while the second phase adopts a unique Pareto solution for the MOO problems, which is characterized by not only comprehensively addressing the trade-offs among multiobjective via the aggregation of both decision makers' preferences and system's properties but also rigorously identifying the best solution via the integration of both absolute improvement degree and relative development balance of the multiobjective system. Besides, the uncertainty degrees of the original data can be well-preserved in the whole framework, offering a rigorous approach for sustainability enhancement under uncertainties. The application of the framework was illustrated by a well-established case study, while the effectiveness and the advantages were verified by the results discussion.