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Author Vasilakou, K.; Billen, P.; Van Passel, S.; Nimmegeers, P. pdf  doi
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  Title A Pareto aggregation approach for environmental-economic multi-objective optimization applied on a second-generation bioethanol production model Type A1 Journal article
  Year (down) 2024 Publication Energy conversion and management Abbreviated Journal  
  Volume 303 Issue Pages 118184-11  
  Keywords A1 Journal article; Economics; Engineering sciences. Technology; Engineering Management (ENM); Intelligence in PRocesses, Advanced Catalysts and Solvents (iPRACS)  
  Abstract Multi-objective optimization is an important decision-making tool for energy processes, as multiple targets need to be achieved. These objectives are usually conflicting since a single solution cannot be optimal for all objectives, resulting in a set of Pareto-optimal solutions. Multiple indicators might be available to describe a sustainability objective, such as the environmental impact which is commonly evaluated by performing a life cycle assessment. In this study, Pareto aggregation is proposed as a method which employs a novel multi-objective optimization-based approach as an alternative to the classically used aggregation in life cycle assessment. This method identifies conflicting environmental indicators and performs an aggregation among those that require a trade-off. An environmental-economic optimization of a second-generation bioethanol plant is used to illustrate and evaluate the proposed method. Process parameters from a biochemical conversion pathway flowsheet simulation model are chosen as optimization variables. To reduce the computational time, surrogate models, based on artificial neural networks, are used. Out of the eighteen ReCiPe Midpoint environmental indicators, five were identified as conflicting, resulting in an aggregated environmental objective, which was then traded off with the economic objective function, chosen as the levelized cost of ethanol. Comparison with the widely used single-score EcoIndicator99 showed that the Pareto aggregation method can reduce most of the environmental indicators by up to 6.5%. This research provides an insight on non-redundant objective functions, aiming at reducing the dimensionality of multi-objective optimization problems, while taking into consideration decision-makers’ preferences.  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Wos 001185718400001 Publication Date 2024-02-10  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0196-8904; 1879-2227 ISBN Additional Links UA library record; WoS full record  
  Impact Factor 10.4 Times cited Open Access  
  Notes Approved Most recent IF: 10.4; 2024 IF: 5.589  
  Call Number UA @ admin @ c:irua:203046 Serial 9216  
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