Volume 18, Issue 4 (12-2021)                   jor 2021, 18(4): 53-71 | Back to browse issues page

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Amin-Tahmasbi H, Dastoureh M. Design of a Robust Multi-Product Multi-Period Green Supply Chain Network. jor 2021; 18 (4) :53-71
URL: http://jamlu.liau.ac.ir/article-1-1927-en.html
Design of a Robust Multi-Product Multi-Period Green Supply Chain Network
H. Amin-Tahmasbi * , M. Dastoureh
Department of Industrial Engineering, Faculty of Technology and Engineering, East of Guilan, University of Guilan, Iran
Abstract:   (1305 Views)
One of the strategic decisions in the supply chain is an efficient network design which has a great impact on reducing costs and increasing customer satisfaction and lead to successful management of the network. Efficient design of green networks also reduces the pollution caused by carbon dioxide emissions. On the other hand, high speed of changes in the business environment has increased uncertainty and ambiguity of the chain. In order to reduce the risk and uncertainty of parameters, it is necessary to use of robust mathematical optimization models. In this research, a multi-objective, multi-product and multi-period model under uncertainty is presented. The first objective function is minimization of transportation costs and the second objective function is to minimize carbon emissions. In this model, both the amount of carbon emissions per time of transport between the plants and the distribution centers and the amount of carbon emissions of the plants and distribution centers are considered. In the constraints, a threshold limit for carbon emissions is considered so that if carbon emissions exceeds the threshold, the implementation of the project is not possible. Then a robust optimization approach is used to model the existing uncertainties. Finally, the results of the robust model are compared with the certain model.
Keywords: Supply Chain Network Design, Green Supply Chain, Robust Optimization, Multi-Product, Multi- Period
Full-Text [PDF 926 kb]   (367 Downloads)    
Type of Study: Research | Subject: Special
Received: 2019/10/7 | Accepted: 2021/05/18
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