Incorporating Fuzzy Learning Approach into a Two-Echelon Sustainable Supply Chain with Imperfect Production Under Environmental and Social Sustainability

Nowadays, supply chain management has challenges in the form of emission reduction, imperfect production, and deteriorating products. In this study, we developed a two-echelon sustainable supply chain for deteriorating products with the inflation’s effect when imperfect items are formed. Through the rework process, some imperfect products are transformed into perfect products. The remaining imperfect items, referred to as “lower quality items,” are sold to the buyer at a reduced price. The buyer purchases both perfect and imperfect items from the producer to sell them through their respective outlets, which have finite capacities. To manage excess perfect quality items, the retailer rents a secondary warehouse with infinite capacity for storage. To manage the uncertainty in the inventory model fuzzy and fuzzy learning is incorporated with fuzzy parameters are taken as triangular fuzzy numbers. The “carbon tax” policy is implemented to reduce emissions by imposing a fee on the carbon content of fossil fuels, thereby incentivizing the use of cleaner energy sources. Preservation and green technology reduce the deterioration rate and carbon emission, respectively. An algorithm is used to solve the proposed model. This study furnishes the numerical illustration to obtain the optimal strategies for green technology investment, cycle time, and preservation technology investment. Through numerical analysis, it is determined that the total profit in the crisp model is $665.32, in the fuzzy model it is $676.473, and in the fuzzy learning model, it reached $680.171. These results clearly indicate that the fuzzy learning approach yielded significantly better outcomes compared to both the crisp and fuzzy models. To highlight the most significant results, an extensive sensitivity assessment is performed over the input parameters. Results indicate that preservation, green, and reliability of the machinery system increase the profit and reduce the emissions.