Fuzzy Set-Based Inventory Model for TPD Demand under effect of Inflation and Carbon Emissions with Partial Backordering

Abstract

Climate change is a global challenge that is gaining attention. Reducing carbon emissions is challenging for achieving both economic growth and sustainable development. This study focuses on optimizing profits in an inventory system, accounting for additional costs due to carbon emissions at various process stages.Deterioration and inflation also affect prices and demand over time. To address these real-world complexities, the authors consider demand to be sensitive to both selling price and time, under inflationary conditions. The model incorporates partial backlogging during shortages to maintain a certain level of customer service even when stock is unavailable.A fuzzy approach is employed to handle the unpredictability associated with cost components. Trapezoidal fuzzy numbers are assigned to the cost variables and are defuzzified using the graded mean integration representation method.The fuzzymodel showsa 3.82% increase inprofit while prices were reduced by 0.27% as compared to the crisp model.The keyobjective of this model is tomaximize profits. Numerical validation and sensitivity analysis are also conducted to evaluate the impact of various changes on the proposed inventory model.