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

Abstract

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.

Multi-Objective Optimization Applications in Chemical Process Engineering: Tutorial and Review

“…The same three objectives have been employed to optimize reactive distillation processes for the eco-efficient production of ethyl levulinate [48]. Xu et al [58] developed a vector-based multi-attribute decision-making method with weighted MOO for enhancing the sustainability of process systems.…”

Specialty Grand Challenge: Multi-Criteria Decision Making for Better Sustainability

“…(Ren et al, 2013;Mehregan et al, 2014). There are also some emerging quantitative models for sustainability enhancement and improvement such as the mathematical framework for optimal process sustainability performance enhancement with the considerations of economic, environmental, social, and technical feasibilities (Moradi-Aliabadi and Huang, 2016), the decision support framework for sustainability enhancement based on the two-layered hierarchical control scheme (Moradi-Aliabadi and Huang, 2018), and the combination of vector-based multiattribute decision-making method and weighted multiobjective optimization technique (Xu et al, 2019). However, there are still various challenges in life cycle sustainability enhancement and improvement: (i) how to incorporate the requirements (sustainability objectives) of the stakeholders in the model for sustainability enhancement and improvement?…”

New Optimization Framework for Improvement Sustainability of Wastewater Treatment Plants

“…This approach aligns with their preferences and streamlines the optimization process by consolidating multiple objectives into a single goal. In the context of the SOA, several methods have been investigated to alleviate computational burdens, such as integrating the decision makers' preferences, implementing normalized constraints, introducing the concept of dominance, employing Pareto filters, and minimizing the distance from the Pareto frontier [27]. However, the SOA can result in information loss and can overlook important trade-offs between conflicting objectives, especially when the stakeholders seek a broader range of options.…”