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dc.contributor.author
Wheeler, Jonathan  
dc.contributor.author
Páez, María Augusta  
dc.contributor.author
Guillén Gosálbez, Gonzalo  
dc.contributor.author
Mele, Fernando Daniel  
dc.date.available
2019-08-09T18:04:51Z  
dc.date.issued
2018-05  
dc.identifier.citation
Wheeler, Jonathan; Páez, María Augusta; Guillén Gosálbez, Gonzalo; Mele, Fernando Daniel; Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains; Pergamon-Elsevier Science Ltd; Computers and Chemical Engineering; 113; 5-2018; 11-31  
dc.identifier.issn
0098-1354  
dc.identifier.uri
http://hdl.handle.net/11336/81327  
dc.description.abstract
Multi-objective optimization (MOO) is widely applied in sustainability problems where several objectives must be accounted for in the analysis. Unfortunately, its complexity grows with the number of objectives, which hampers its practical use. In this paper, we simplify MOO problems via their combination with multi-attribute decision-making (MADM) methods. The approach identifies a unique Pareto solution of the MOO problem, which best reflects the decision-makers’ preferences, by using weighting factors generated via four well-known MADM methods: SWING, SMART, AHP and TRADE OFF. The capabilities of this approach are illustrated through its application to the design and planning of a sugar/ethanol supply chain using questionnaires filled in by academic experts in the problem. We find that the weights obtained using MADM algorithms may well differ from the ones given by standard life-cycle assessment methods employed in systems engineering problems. Overall, our approach simplifies the MOO problem by identifying solutions consistent with the decision-makers’ preferences and by providing valuable insight on how these preferences are articulated in practice.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Pergamon-Elsevier Science Ltd  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Sustainability  
dc.subject
Multi-Criteria Optimization  
dc.subject
Environmental Impact  
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Biorefinery Design  
dc.subject
Decision-Making  
dc.subject.classification
Ingeniería de Procesos Químicos  
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Ingeniería Química  
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INGENIERÍAS Y TECNOLOGÍAS  
dc.title
Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2019-08-06T18:17:09Z  
dc.journal.volume
113  
dc.journal.pagination
11-31  
dc.journal.pais
Estados Unidos  
dc.description.fil
Fil: Wheeler, Jonathan. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina  
dc.description.fil
Fil: Páez, María Augusta. University of Manchester; Reino Unido  
dc.description.fil
Fil: Guillén Gosálbez, Gonzalo. Imperial College London; Reino Unido  
dc.description.fil
Fil: Mele, Fernando Daniel. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ingeniería en Procesos y Gestión Industrial; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; Argentina  
dc.journal.title
Computers and Chemical Engineering  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://linkhttps://www.sciencedirect.com/science/article/pii/S0098135418300759?via%3Dihub#!inghub.elsevier.com/retrieve/pii/S0098135418300759  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://doi.org/10.1016/j.compchemeng.2018.02.010