A Supply Chain Model with Carbon Emissions and Preservation Technology for Deteriorating Items under Trade Credit Policy and Learning in Fuzzy

In this study, a supply chain model is proposed with preservation technology under learning fuzzy theory for deteriorating items where the demand rate depends on the selling price and also treats as a triangular fuzzy number. The deterioration rate of any item cannot be eliminated due to its natural process, but it can be controlled with the help of preservation technology. Some harmful gases are emitted during the preservation process due to deteriorating items that harm the environment. In general, it can be easily seen that most of the sellers offer a trade credit policy to their regular buyers. In this paper, the retailer’s inventory stock reduces due to demand and deterioration. It is also assumed that some units are defective due to machine defects or delivery inefficiency. The retailer accepted the policy of trade credit offered by the seller. The aim of this paper is to enhance the profit of the supply chain partners. We proposed a theorem to get the optimal values of the selling price and cycle length. The retailer’s total profit is a function of selling price and cycle length, and the retailer’s total profit is optimized with respect to selling price and cycle length under trade-credit. Numerical examples are also presented for the validation of the present study, and sensitivity analysis is also discussed to know the robustness of the supply chain model. Managerial insight and observation have been given in the sensitivity section. Limitations and future work of this paper have been presented in the conclusion section.