Design of multi-objective multi-product multi period green supply chain network with considering discount under uncertainty

Document Type : Research Paper

Authors

1 Department of Industrial Engineering, Kharazmi University

2 Department of Industrial Engineering, University of Tehran

Abstract

In today’s world, changes in the economy and industry field occur in higher speed compared to the past time. The main aim of organizations and companies is to preserve and increase the benefit as well as survive in the commercial fields. This matter has caused in large scale because of that companies the globalization, economic activity along with the rapid Increment of the technical and restricted sources to compete closely together. For the companies, the competitive benefits, for example as to become efficient related to the affairs such as supply chain. Additionally, because of governmental rules, green affairs and development the social responsibility concept, management the closed loop supply chain field has attained many research interests. Closed loop Supply chain involve forward and reverse both together and the main aim of it’s design is to mix up the environmental observations with the traditional supply chain using accumulating the used products and operations related to the them as well. In this paper a multi objective, multi period multi product closed loop supply chain mathematical model considering green matters and compensable shortage as well as discounts has been developed. Firstly, closed loop supply chain mathematical model has been solved using three multi objective decision maker methods and numerical results have been reported in large scale. Secondly, regarding to the uncertainty of the parameters, the robust optimization model related to the main model has been formed and solved using multi objective decision maker methods, finally the best method for deterministic and uncertain model using filtering has been chosen.

Keywords

Main Subjects

References

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Journal of Industrial Engineering Research in Production Systems
Volume 6, Issue 13
Winter and Spring 2019
March 2019
Pages 119-137

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