Abstract

Nowadays, many organizations are trying to balance the social, environmental, and economic aspects of their supply chains to gain competitive advantages against their rivals and have a sustainable supply chain. Steel is one of the most critical raw materials practically used in every aspect of our life, directly or indirectly influencing the industry and economy of a country. The final products of the steel industry can be reused at the end of their lifecycle, making the principles of reverse logistics applicable in the supply chain and turning it to a closed-loop supply chain. In this research, a multi-objective linear mathematical model under uncertainty is developed to optimize a steel sustainable closed-loop supply chain. The existed uncertainty is modeled through a scenario-based method in the stochastic environment, and the proposed multi-objective model is developed following a fuzzy goal programming approach. A real case study is explored in one of the active steel supply chains in Iran to validate the model. The model optimizes total profit, energy, and water consumption, CO2 emission, job opportunity created, and lost working days through determining optimal production technology, whether retailers get changed to hybrid centers or not, and the flow of material and products. The final results show that a mere 1% decrease in the profit can alleviate the harmful environmental effects by 5%. Finally, several managerial implications derived from final results and sensitivity analysis are discussed to provide insights for industry leaders who desire to increase their profits with regard to environmental and social effects.

Full Text
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