A serial inventory system with supplier selection and order quantity allocation considering transportation costs

• Supplier selection and order quantity allocation in a serial supply chain system.
• Transportation costs are based on full truckload freight rates.
• Objective is to minimize average cost and find order quantities for selected suppliers.
• A mixed integer nonlinear programming formulation of the problem is provided.
• Advantages of using an integrated approach versus a sequential approach are provided.

Given the importance of incorporating transportation costs in inventory replenishment and supplier selection decisions, this article addresses the issue of supplier selection and order quantity allocation in a multi-stage serial supply chain system with multiple suppliers considering inventory replenishment, holding, and transportation costs simultaneously. We propose a mixed integer nonlinear programming model to determine the optimal inventory policy for the stages in the supply chain and allocation of orders among the suppliers at the initial stage. Transportation costs between consecutive stages are modeled using a piecewise constant setup cost structure arising from a full truckload freight rate cost model. Vehicles of different capacities are available to transport materials from the suppliers to the manufacturing facility and between the remaining stages of the supply chain. The usefulness of the model is discussed with an example. Sensitivity analysis is carried out to determine the effect of cost parameters on supplier order allocation. The analysis shows that the selection of suppliers and the corresponding order quantities are affected by the variations in supply chain costs parameters. In addition, the advantages of using an integrated approach versus a sequential approach for inventory replenishment and supplier selection decisions are shown. Computational results show that the integrated approach yields average savings of 4.88% in total cost and 15.31% in logistics costs over the sequential approach.