فهرست نشریات علمی دسترسی آزاد ایران

In today’s competitive markets, determining the optimum distribution centers, delivery routes, and inventory levels is crucial for cold chain logistics of perishable products to reduce costs as well as backorder rate. Meanwhile, a new bi-phase mixed integer non-linear programming model-based robust possibilistic approach is developed by goals of minimizing total costs and reducing the backorder rate for key customers to solve the hub location-routing model for a cold chain of perishable products. To address the issue, the augmented ε-constraint method is considered to construct a single objective model, and the obtained Pareto optimal points are analyzed. Additionally, the robust possibilistic approach is executed to cope with imprecise demand in the presented bi-phase hub location-routing model. To represent the verification and applicability of the proposed approach, a case study on cold chain logistics of perishable products is regarded. Finally, a comparative analysis is considered to compare the obtained results from the proposed approach with real case information. This validation process is defined by schematically reporting the trend comparison results over the entire planning horizon. Moreover, the obtained results represents that the proposed approach can enhance the objective function by reducing the 22% of total costs, improved the backorder level by 24%, the number of deteriorating items decreased by 16.48%, and the inventory levels enhanced by 12.86% regarding the current practice.