Design of a Cooperative Sustainable Three-Echelon Supply Chain under Uncertainty in CO2 Allowance
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Título: | Design of a Cooperative Sustainable Three-Echelon Supply Chain under Uncertainty in CO2 Allowance |
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Autor/es: | Lujan Garcia-Castro, Florencia | Ruiz-Femenia, Rubén | Salcedo Díaz, Raquel | Caballero, José A. |
Grupo/s de investigación o GITE: | Computer Optimization of Chemical Engineering Processes and Technologies (CONCEPT) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Ingeniería Química |
Palabras clave: | Uncertainty of CO2 allowance prices | Stochastic model | Optimum supply chain management | Cooperative game theory | ARIMA price prediction | Scenario reduction | ScenRed | K-means |
Fecha de publicación: | 12-ago-2022 |
Editor: | American Chemical Society |
Cita bibliográfica: | ACS Sustainable Chemistry & Engineering. 2022, 10(34): 11098-11105. https://doi.org/10.1021/acssuschemeng.2c01270 |
Resumen: | Driven by the growing concern regarding greenhouse gas emissions, in this work, we provide a robust stochastic model for the design of a cooperative supply chain (SC) under uncertainty in CO2 allowance prices from the European Union Emissions Trading System (EU ETS). During the last years, CO2 allowance prices have undergone unexpected changes, having strong impact on the design and management of optimal SC. The consideration of uncertainty in the allowance prices has therefore become more important. We use an autoregressive integrated moving average (ARIMA) model to predict future allowance prices. A full discretization of the underlying probability space leads to a number of scenarios far too large to be handled, so we compare two approaches to reduce the number of scenarios to a feasible maximum, the ScenRed algorithm and K-means clustering. The obtained results are compared with a deterministic approach that is widely studied in the literature, showing an increase in the benefits and a reduction of emissions. |
Patrocinador/es: | The authors gratefully acknowledge financial support to the Conselleria de Innovacion, Universidades, Ciencia y Sociedad Digital of the Generalitat Valenciana, Spain, under project PROMETEO/2020/064. |
URI: | http://hdl.handle.net/10045/126154 |
ISSN: | 2168-0485 |
DOI: | 10.1021/acssuschemeng.2c01270 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2022 The Authors. Published by American Chemical Society. Creative Commons Attribution 4.0 International License (CC BY 4.0) |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1021/acssuschemeng.2c01270 |
Aparece en las colecciones: | INV - CONCEPT - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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Lujan_etal_2022_ACSSustainableChemEng.pdf | 3,09 MB | Adobe PDF | Abrir Vista previa | |
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