Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains

Autores
Wheeler, Jonathan; Páez, María Augusta; Guillén Gosálbez, Gonzalo; Mele, Fernando Daniel
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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.
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
Fil: Páez, María Augusta. University of Manchester; Reino Unido
Fil: Guillén Gosálbez, Gonzalo. Imperial College London; Reino Unido
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
Materia
Sustainability
Multi-Criteria Optimization
Environmental Impact
Biorefinery Design
Decision-Making
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/81327
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chainsWheeler, JonathanPáez, María AugustaGuillén Gosálbez, GonzaloMele, Fernando DanielSustainabilityMulti-Criteria OptimizationEnvironmental ImpactBiorefinery DesignDecision-Makinghttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2Multi-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.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; ArgentinaFil: Páez, María Augusta. University of Manchester; Reino UnidoFil: Guillén Gosálbez, Gonzalo. Imperial College London; Reino UnidoFil: 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; ArgentinaPergamon-Elsevier Science Ltd2018-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/81327Wheeler, 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; 11-310098-1354CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://linkhttps://www.sciencedirect.com/science/article/pii/S0098135418300759?via%3Dihub#!inghub.elsevier.com/retrieve/pii/S0098135418300759info:eu-repo/semantics/altIdentifier/url/https://doi.org/10.1016/j.compchemeng.2018.02.010info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:47:52Zoai:ri.conicet.gov.ar:11336/81327instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:47:52.918CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains
title Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains
spellingShingle Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains
Wheeler, Jonathan
Sustainability
Multi-Criteria Optimization
Environmental Impact
Biorefinery Design
Decision-Making
title_short Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains
title_full Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains
title_fullStr Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains
title_full_unstemmed Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains
title_sort Combining multi-attribute decision-making methods with multi-objective optimization in the design of biomass supply chains
dc.creator.none.fl_str_mv Wheeler, Jonathan
Páez, María Augusta
Guillén Gosálbez, Gonzalo
Mele, Fernando Daniel
author Wheeler, Jonathan
author_facet Wheeler, Jonathan
Páez, María Augusta
Guillén Gosálbez, Gonzalo
Mele, Fernando Daniel
author_role author
author2 Páez, María Augusta
Guillén Gosálbez, Gonzalo
Mele, Fernando Daniel
author2_role author
author
author
dc.subject.none.fl_str_mv Sustainability
Multi-Criteria Optimization
Environmental Impact
Biorefinery Design
Decision-Making
topic Sustainability
Multi-Criteria Optimization
Environmental Impact
Biorefinery Design
Decision-Making
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv 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.
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
Fil: Páez, María Augusta. University of Manchester; Reino Unido
Fil: Guillén Gosálbez, Gonzalo. Imperial College London; Reino Unido
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
description 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.
publishDate 2018
dc.date.none.fl_str_mv 2018-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/81327
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
0098-1354
CONICET Digital
CONICET
url http://hdl.handle.net/11336/81327
identifier_str_mv 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
0098-1354
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://linkhttps://www.sciencedirect.com/science/article/pii/S0098135418300759?via%3Dihub#!inghub.elsevier.com/retrieve/pii/S0098135418300759
info:eu-repo/semantics/altIdentifier/url/https://doi.org/10.1016/j.compchemeng.2018.02.010
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
publisher.none.fl_str_mv Pergamon-Elsevier Science Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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