4.6 Article

A Multiobjective Optimization-Based Approach for Optimal Chemical Product Design

期刊

INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
卷 53, 期 44, 页码 17429-17444

出版社

AMER CHEMICAL SOC
DOI: 10.1021/ie502906a

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  1. University of Nottingham Research Committee

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Over the past decades, chemical products have been constantly evolving to satisfy the demands and requirements of market. Hence, there is a continuous search for new and improved products which possess enhanced properties for specific applications. The conventional approach to produce new chemical products with specific functionality is based on design heuristics, experimental studies, and expert judgments. Other than the traditional methods, chemical products can also be designed by identifying the properties of the product by using the reverse engineering approach. This approach first identifies the needs to fulfill, and then searches for molecule/s that possess properties which can meet the target needs. On the basis of the approach, an optimal chemical product can be designed by identifying the molecule/s with the best properties that correspond with the target functionalities of the product. Most of the established chemical product design methodologies focus on optimizing a single property of a product. It is mindful that in some situations, there are several important product properties to be considered in order to design an optimized chemical product. In cases where more than one product property is to be considered and optimized, a multiobjective optimization design problem is needed to optimize all the important targeted properties simultaneously. In the previous works, the product properties were optimized based on the weighting factors assigned by decision makers. This method tends to be biased as it depends heavily on expert judgments or personal preferences. To address this problem, a systematic methodology for the design of chemical products with optimal properties has been developed in this paper. A fuzzy optimization approach and molecular design techniques are adapted to address the above-mentioned design problem. Maxmin aggregation and two-phase approaches are incorporated into fuzzy optimization approach, and the solutions generated from both approaches are compared. A case study on the design of a solvent used in a gas sweetening process is presented to illustrate the developed methodology in chemical product design.

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