Design and Analysis of Supply Chain Networks with Low Carbon Emissions

• Published in: Computational economics Vol. 52; no. 4; pp. 1353 - 1374
• Main Authors: Kuo, Tsai-Chi, Tseng, Ming-Lang, Chen, Hsiao-Min, Chen, Ping-Shun, Chang, Po-Chen
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2018; Springer Nature B.V
• Subjects: Behavioral/Experimental Economics; Carbon; Carbon footprint; Computer Appl. in Social and Behavioral Sciences; Decision making; Economic Theory/Quantitative Economics/Mathematical Methods; Economics; Economics and Finance; Emissions; Environmental impact; Greenhouse effect; Greenhouse gases; Math Applications in Computer Science; Mathematical models; Multiple objective analysis; Operations Research/Decision Theory; Pareto optimum; Predictions; Supply; Supply chains; Low carbon supply chain networks; Greenhouse gas emission; Normal constraint method
• ISSN: 0927-7099; 1572-9974
• DOI: 10.1007/s10614-017-9675-7

Low carbon supply chain network design is a multi-objective decision-making problem that involves a trade-off between low carbon emissions and cost. This study calculates the carbon footprint, wherein the greenhouse gases (GHGs) emissions data are based on carbon footprint standards. Many firms have redesigned their supply chain networks to reduce their GHG emissions. Furthermore, the production capacities and costs are collected and evaluated by using Pareto optimal solutions. In order to achieve the optimal solutions, a normal constraint method is used to formulate a mathematical model to meet two objectives: low carbon emissions and low cost. A case study is also presented to demonstrate the predictive ability of this model. The result shows that it is possible to reduce carbon emissions and lower cost simultaneously.