A ROBUST MULTI-OBJECTIVE MODEL FOR MANAGING THE DISTRIBUTION OF PERISHABLE PRODUCTS WITHIN A GREEN CLOSED-LOOP SUPPLY CHAIN

The required processes of supply chain management include opti-mal strategic, tactical, and operational decisions, all of which have important economic and environmental effects. In this regard, efficient supply chain plan-ning for the production and distribution of perishable productsis of particular importance due to its leading role in the human food pyramid. One of the main challenges facing this chain is the time when products and goods are de-livered to the customers and customer satisfaction will increase through this.In this research, a bi-objective mixed-integer linear programming (MILP)model is proposedto design a multi-level, multi-period, multi-pro duct closed-loop supply chain (CLSC) for timely production and distribution of perishable products, taking into account the uncertainty of demand. To face the model uncertainty, the robust optimization (RO) method is utilized. Moreover, to solve and val-idate the bi-objective model in small-size problems, the -constraint method (EC) is presented. On the other hand, a Non-dominated Sorting Genetic Al-gorithm (NSGA-II) is developed for solving large-size problems. First, the deterministic and robust models are compared by applying the suggested solu-tions methods in a small-size problem, and then,the proposed solution methods are compared in large-size problems in terms of different well-known metrics. According to the comparison, the proposed model has an acceptable perfor-mance in providing the optimal solutions and the proposed algorithm obtains efficient solutions.Finally, managerial insights are proposed using sensitivity analysis of important parameters of the problem.