<p>This study presents an integrated framework that enhances supply chain efficiency in the automobile sector by incorporating manufacturing and advertisement-dependent demand forecasting whilst addressing carbon emissions and partial backlogging with a learning effect. A novel decision-making model based on interval-valued triangular intuitionistic fuzzy numbers (IVTIFNs) is proposed to handle uncertainty effectively. The model optimizes inventory management by evaluating objective functions and implementing a simulated annealing technique to minimize overall costs. A numerical example is described, and sensitivity analysis is done on parameters affecting the overall cost. The findings highlight the significance of advertisement-driven demand in supply chain optimization and its potential role in balancing financial efficiency with environmental sustainability.</p>