Fuzzy reverse logistics inventory model of smart items with two warehouses of a retailer considering carbon emissions

Running the business smoothly for protecting environment is a significant challenge, on which industries are trying something to do at their level best. Reverse logistics play an important role in system design by reducing environmental consequences and increasing economic social impacts. Given recent fluctuations of market, production cost ordering considered triangular fuzzy numbers this study. Customers’ demand met right time, there no shortage items; thus, attention can be paid two warehouses retailer. The setup costs Purchasing deterioration affected learning effects, lead decrease total cost. Inflation problem market because manufacturing, remanufacturing, retailers all affected. This study proposes reverse model so that customers resolve complaints about defective items carbon emissions under warehouses. Numerical results show more economically beneficial than crisp model, finds saw difference 0.34% Two numerical examples illustrate study, sensitivity analysis performed using tables graph.