Fuzzy Intelligence Inventory Decision Optimization Model of Sustainability and Green Technologies for Mixed Uncertainties of Carbon Emission

In many areas, carbon cap-and-trade and carbon offsets are frequent and significant mechanisms for reducing carbon emissions. Furthermore, particular capital investments in green technologies can efficiently cut carbon emissions from corporate activities. However, such capital investments are expensive, and not all businesses/company can afford them. As a result, if all members of a supply chain agree to share facility investments, the supply chain can cut carbon emissions while also increasing profit. This study utilized crisp and fuzzy models to fix perishable products in the production process. The suggested model, for study is solved using python in machine learning. To cut carbon emissions and increase the total value of the supply chain system, we planned to integrate manufacturing, distribution, replenishment, and technology. Several cases are simulated, and the key parameters are subjected to sensitivity analysis. Under various carbon emission rules, the optimal solutions and joint total profit are also compared. Companies should be able to share risks by co-investing and building sustainable supply chains as a part of the future carbon emission control trend.