Robust Optimization of the Forward / Reverse Model of Multi-objective, Multi-product and Multi-period Green Supply Chain in Conditions of Uncertainty

Environmental concerns and significant changes in the business environment have led to the design of a supply chain network integrating environmental and economic factors in conditions of uncertainty. The proposed model will assist business owners in supplying some of their raw materials by recycling returned products from customers. Therefore, this study has developed the design of multi-objective, multi-period forward / reverse / inverse model for green supply chain in the form of a mixed linear programming model under demand uncertainty and the cost of transportation and return products to assess economic and environmental costs. First, deterministic mixed integerlinear programming (MILP) model is solved by solving multi-objective optimization by GAMS software. In the next step, the robust optimization model of the proposed model was presented by considering the uncertainties in the demand parameters, transportation costs and return products, and the results of solving the robust model were obtained. In the end, it was shown that the Torabi Hosseini method had the best performance in terms of the quality of the answers and the average computational time for the deterministic and robust models.

کلیدواژه ها:

Green Supply Chain ، Robust Optimization ، Forward / Reverse Logistics ، Under Uncertainty.