Developing an inventory model including shortage for the recycling process using fuzzy logic approach

After the end of its lifespan usable their the products are made reusable by going through many processes according to the type and/or raw material of the product. This process is defined as recycling and provides many benefits to human beings in the environmental, economic and social areas. The importance of the recycling industry is increasing worldwide due to its benefits such as environmental protection, reduction of raw material need, economical use of resources and reduction of pollution. In this study, a fuzzy inventory model including the recycling process is proposed. Firstly, an expanded production/recycling model with fixed demand and return rates developed by Dobos and Richter (2003) is rearranged in terms of the waste disposal process and the level of stock to be created. In the second stage, a new stock model was proposed by adding the shortages assumption to the model. Finally, the model is fuzzified by taking the demand and all cost parameters as triangular fuzzy numbers. Thus, fuzzy stock model was developed as a second model proposal. The fuzzy model is defuzzification by the graded mean integration representation (GMIR) method. Optimal solution values calculated for the total cost(br) (CU), the length of shortages cycle (tp), length of a production-recycling cycle (T) were expressed crisp value. When the results of the experimental application are evaluated, it has been observed that the proposed fuzzy stock model gives more successful results than the deterministic stock model based on.