Abstract
The conditions of global competition and environmental sensitivities have made organizations and factories to collect returned products, in such a way that these organizations have tried to rehabilitate, recycle, or destroy these products in order to protect the environment. This paper propose a mathematical model for the green closed-loop supply chain network of heavy tire by considering the economic pricing of its products under conditions of uncertainty, which economically determines the price and leads to more profitability. In addition, the relevant model is a two-objective fuzzy model, the first objective of which is to minimize costs and maximize profits, and the second objective is to minimize environmental issues. The proposed model can also determine the optimal location of each center based on potential locations, the optimal amount of production, distribution, collection, recycling, as well as the reproduction of products. The ε-constraint method is used to solve the model with two objective functions; this method ensures strong Pareto optimal answers and prevents weak Pareto answers. Independent two-sample t-test is used to verify the results of certain and uncertain models in the studied model. In order to evaluate the effectiveness and profitability of the proposed method, a case study in the field of heavy tires is finally used, through which very useful results are obtained.
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Javad Amirian: methodology, software, formal analysis, data curation, writing original draft, writing review and edit, and visualization
Hossein Amoozad Khalili: conceptualization, supervision, software, methodology, formal analysis, data curation, writing original draft, and visualization
Ahmad Mehrabian: methodology, validation, and writing review and edit
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Amirian, J., Amoozad Khalili, H. & Mehrabian, A. Designing an optimization model for green closed-loop supply chain network of heavy tire by considering economic pricing under uncertainty. Environ Sci Pollut Res 29, 53107–53120 (2022). https://doi.org/10.1007/s11356-022-19578-0
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DOI: https://doi.org/10.1007/s11356-022-19578-0