The supply chain network design has attracted the attention of many researchers during recent years. This paper presents a new bi-objective mixed-integer linear programming (MILP) model to integrate procurement, production and distribution planning under uncertainty. This model is set up for the network of a multi-echelon, multi-product, multi-channel, multi-period supply chain with regard to two conflicting objectives, which minimize the costs and minimize the sum of backorders and surpluses of products in all periods using “activity-based costing and the total cost of ownership” and “JIT” concepts, respectively. To solve the presented model, an interactive fuzzy approach is used. The associated results show the amount of purchasing of each supplier, the quantity of producing, the inventory of raw materials and products, backorder or surplus delivery of goods, the mode of transportation, the amount of goods transported between facilities and suppliers used in each period. In addition, a numerical example is presented to demonstrate the applicability of the presented model and exhibit the efficiency of the proposed interactive fuzzy approach. Finally, the results and conclusion are provided.