A robust Tri-Objective optimization to supply chain configuration under Vendor-Managed inventory policy considering supply chain visibility

This paper presents a novel tri-objective robust Mixed-Integer Linear Programming (MILP) to a two-echelon supply chain configuration. It simultaneously considers the Vendor-Managed Inventory (VMI) policy and the Supply Chain Visibility (SCV), under uncertain demand. The objectives are to concurrently maximize the total visibility, minimize the number of deficient products and minimize the total cost. The LP-metric is then applied to deal with the tri-objectiveness of the model. The results show that the proposed approach successfully es-tablishes robustness by deteriorating the optimal values of the objective functions as the cost of robustness. A sensitivity analysis reveals that the level of uncertainty has the greatest impact on the network's cost and deficiency of objective functions. However, the greatest effect on the SCV function is the change in the lower visibility threshold parameter. Moreover, the value of the deficiency rate parameter has the least impact on all three objective functions and has no impact on the visibility of the supply chain.

Automated summary

This paper proposes a novel tri-objective robust MILP model for a two-echelon supply chain configuration considering Vendor-Managed Inventory (VMI) policy and Supply Chain Visibility (SCV) under uncertain demand. The objectives are to maximize total visibility, minimize deficient products, and minimize total cost. The LP-metric is used to handle the tri-objectiveness of the model. The results show that the proposed approach successfully establishes robustness by deteriorating the optimal values of the objective functions as the cost of robustness. A sensitivity analysis reveals that uncertainty has the greatest impact on network cost and deficiency of objective functions. The change in the lower visibility threshold parameter has the greatest effect on the SCV function.