Desining a Multi-Objective Mathematical Model of Cumulative Production Planning in Reverse Supply Chain With Production Quality Function Under Uncertainty and Using MPSOGA Tran-Innovation Algorithm (High-Tech Industry Case Study)

In the present paper, the cogeneration program in the form of an inverse supply chain using multi-objective mathematical modeling in conditions of uncertainty is considered. The supply chain process consists of three levels including suppliers, manufacturers and customers, and there is a maintenance center and a reconstruction center. The first objective function of the model is to minimize costs; the second objective is to maximize the quality of the product. In the mentioned supply chain, the third and fourth objective functions represent minimizing the total weight of the maximum shortage among customers and maximizing the total weight of the minimum supply of goods from suppliers. In this model, the third objective function is designed in conditions of uncertainty using the Malloy stabilization method based on scenario writing. It is called MPSOGA.