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A robust-heuristic optimization approach to a green supply chain design with consideration of assorted vehicle types and carbon policies under uncertainty

  • Adoption of carbon regulation mechanisms facilitates an evolution toward green and sustainable supply chains followed by an increased complexity. Through the development and usage of a multi-choice goal programming model solved by an improved algorithm, this article investigates sustainability strategies for carbon regulations mechanisms. We first propose a sustainable logistics model that considers assorted vehicle types and gas emissions involved with product transportation. We then construct a bi-objective model that minimizes total cost as the first objective function and follows environmental considerations in the second one. With our novel robust-heuristic optimization approach, we seek to support the decision-makers in comparison and selection of carbon emission policies in supply chains in complex settings with assorted vehicle types, demand and economic uncertainty. We deploy our model in a case-study to evaluate and analyse two carbon reduction policies, i.e., carbon-tax and cap-and-trade policies. The results demonstrate that our robust-heuristic methodology can efficiently deal with demand and economic uncertainty, especially in large-scale problems. Our findings suggest that governmental incentives for a cap-and-trade policy would be more effective for supply chains in lowering pollution by investing in cleaner technologies and adopting greener practices.

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Metadaten
Author:Dmitry IvanovORCiD
URN:urn:nbn:de:kobv:b721-opus4-34044
URL:https://link.springer.com/article/10.1007%2Fs10479-021-03985-6
DOI:https://doi.org/10.1007/s10479-021-03985-6
Publisher:Springer Nature
Document Type:Article
Language:English
Date of first Publication:2021/03/06
Publishing Institution:Hochschulbibliothek HWR Berlin
Release Date:2021/12/27
Tag:Green supply chain; Improved multi-choice goal programming; Robust-heuristic optimization; Sustainable logistics; Sustainable supply chain
Issue:Ann Oper Res (2021)
Institutes:FB I - Wirtschaftswissenschaften
Open Access Publikationen (DINI-Set):open_access
Open Access Publikations financed by DEAL Project:hybrid
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International