A Scenario-Based Inventory Optimization Approach for a Multi- Echelon Network Considering Lateral Transshipment

Nowadays, Companies have to deal with an uncertain demand which is more difficult to handle when it has a non-stationary pattern. Simultaneous decrease of customer service and increase of stock costs are the most significant effects of such demand uncertainty. To deal with this issue, inventory optimization models must be adapted to cover a multi-echelon network structure and to consider alternative sourcing strategies such as lateral transshipment and multiple sourcing. In this work, a scenario-based modeling approach is proposed to solve a multi-echelon inventory optimization problem considering a non-stationary demand. The model considers minimizing the total cost that is composed of inventory holding, transportation and backordering costs. Lateral transshipment is applied to reduce inventory backorders. Another important factor in inventory optimization is flexibility. Sourcing from multiple distribution centers is a strategy to reduce supply disruption risk and to cover the possible shortage. Multiple-sourcing is considered in this research and has been analyzed in different scenarios. Several test problems are generated by Monte Carlo scenario samples and corresponding sample average approximations programs, are solved to validate the applicability of the model and to evaluate the impact of lateral transshipment and multiple sourcing.