A Stackelberg Game Approach in Supply Chain for Imperfect Quality Items with Learning Effect in Fuzzy Environment

Abstract

In recent decades, researchers have effectively worked on seeking optimal policies under supply chain management for attaining practical and powerful outcomes. This paper studies supply chain model for imperfect quality items in which demand depends upon the buyer’s price and marketing cost. The buyer segregates the defective items from supplied lot by seller and sell them at discounted price. In today’s scenario, learning effect methodology has become a promotional tool in supply chain management. It impacts profit or loss of the members of the supply chain. The rapid change in the life cycle of product makes the parameters of the supply chain models more and more uncertain. Fuzzy analysis becomes a powerful tool to deal such type of vague or uncertain parameters in computing form. It examines the better assessment and performance of imprecise parameters. Keeping in view, some supply chain models for imperfect quality items have been developed by considering learning effect under fuzzy environment. A non-cooperative Stackelberg game theoretic approach is used to find the optimal decision variables and optimum profit of the supply chain members in fuzzy environment. Various numerical results with sensitivity analysis have been explained to justify the model.