Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks
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http://hdl.handle.net/10045/39634
Título: | Handling of Uncertainty in Life Cycle Inventory by Correlated Multivariate Lognormal Distributions: Application to the Design of Supply Chain Networks |
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Autor/es: | Labarta, Juan A. | Salcedo Díaz, Raquel | Ruiz-Femenia, Rubén | Guillén Gosálbez, Gonzalo | Caballero, José A. |
Grupo/s de investigación o GITE: | Computer Optimization of Chemical Engineering Processes and Technologies (CONCEPT) | Estudios de Transferencia de Materia y Control de Calidad de Aguas (ETMyCCA) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Ingeniería Química |
Palabras clave: | Lognormal distribution | Life cycle assessment | Risk management | Multi-objective optimization | Sustainable supply chain |
Área/s de conocimiento: | Ingeniería Química |
Fecha de publicación: | jun-2014 |
Resumen: | In this work, we analyze the effect of incorporating life cycle inventory (LCI) uncertainty on the multi-objective optimization of chemical supply chains (SC) considering simultaneously their economic and environmental performance. To this end, we present a stochastic multi-scenario mixed-integer linear programming (MILP) coupled with a two-step transformation scenario generation algorithm with the unique feature of providing scenarios where the LCI random variables are correlated and each one of them has the desired lognormal marginal distribution. The environmental performance is quantified following life cycle assessment (LCA) principles, which are represented in the model formulation through standard algebraic equations. The capabilities of our approach are illustrated through a case study of a petrochemical supply chain. We show that the stochastic solution improves the economic performance of the SC in comparison with the deterministic one at any level of the environmental impact, and moreover the correlation among environmental burdens provides more realistic scenarios for the decision making process. |
Descripción: | Poster presented in the 24th European Symposium on Computer Aided Process Engineering (ESCAPE 24), Budapest, Hungary, June 15-18, 2014. |
Patrocinador/es: | The authors wish to acknowledge support from the Spanish Ministry of Science and Innovation (CTQ2012-37039-C02-02). |
URI: | http://hdl.handle.net/10045/39634 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/conferenceObject |
Derechos: | Licencia Creative Commons Reconocimiento-NoComercial-SinObraDerivada 4.0 |
Aparece en las colecciones: | INV - CONCEPT - Comunicaciones a Congresos, Conferencias, etc. INV - ETMyCCA - Comunicaciones a Congresos, Conferencias, etc. |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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Poster_ESCAPE24_Uncert_LCA.pdf | 166,1 kB | Adobe PDF | Abrir Vista previa | |
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