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Currently, levels of production and disposal for communication devices such as smartphones are continuing to increase. In the life cycle of a smartphone, the majority of greenhouse gas (GHG) emissions are generated in the material production stage. To recover the GHG emissions from end-of-life (EOL) products such as smartphones, manufacturers have to recycle EOL products. However, smartphones on the market undergo little recycling because costs related to recycling, transportation, and facilities are very high. Therefore, the decision maker (DM) has to design a reverse supply chain network for collecting EOL products from users and transporting them to recovery or disposal facilities not only environmentally friendly but also economically feasible. This study applies a bi-objective reverse supply chain network design to material-based GHG volumes and related costs applying a multi-criteria decision-making methods as linear physical programming (LPP) to design a reverse supply chain network in the case of smartphones. First, the reverse supply chain network is modeled for recycling EOL smartphones, and a case study based on literatures and life cycle assessment are prepared. Next, the objective functions are set and formulated to minimize the total volume of material-based GHG volume and the total cost using LPP and integer programming. Finally, numerical experiments on the reverse supply chain are conducted and evaluated.

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