A bi-objective multi-echelon supply chain model with Pareto optimal points evaluation for perishable products under uncertainty

Selecting the most suitable optimal point among the Pareto optimal points could help the experts to make an appropriate decision in an uncertain and complex situation. In this paper, an evaluating and ranking approach is proposed based on hesitant fuzzy set environment to assess the obtained Pareto optimal points from the proposed bi-objective multi-echelon supply chain model with locating distribution centers. In this respect, the proposed model has elaborated for perishable products based on fuzzy customers' demand. To address the issue, the possibilistic chance constraint programming approach has manipulated based on the trapezoidal fuzzy membership function. Moreover, the proposed hesitant fuzzy ranking approach is constructed based on group decision analysis and the last aggregation approach. Thereby, the last aggregation approach by aggregating the experts' opinions in last step could prevent the data loss. However, a case study about the perishable dairy products is considered to indicate the applicability of the proposed bi-objective multi-echelon supply chain model with locating distribution centers. Finally, a comparative analysis is provided between the obtained results and the current practice to show the feasibility and efficiency of the proposed model.