An Application of a Cost Minimization Model in Determining Safety Stock Level and Location

In recent decades, the lean methodology and the development of its principles and concepts have widely been applied in supply chain management. One of the most important strategies of being lean is having efficient inventory within the whole supply chain. Managing inventory efficiently requires appropriate management of safety stock in order to compensate the weakness of the supply chain for product availability.A nonlinear cost minimizationsafety stock model with the objective of minimizing the total logistics cost is developed in this paper. This modelis also applied to a real-world case company which is a manufacturer.The model results in optimum levels and locations of safety stock within the company’s supply chain in order to minimize total logistics costs

A simulation-optimization approach for a service-constrained multi-echelon distribution network

Academic research on (s,S) inventory policies for multi-echelon distribution networks with deterministic lead times, backordering, and fill rate constraints is limited. Inspired by a real-life Dutch food retail case we develop a simulation-optimization approach to optimize (s,S) inventory policies in such a setting. We compare the performance of a Nested Bisection Search (NBS) and a novel Scatter Search (SS) metaheuristic using 1280 instances from literature and we derive managerial implications from a real-life case. Results show that the SS outperforms the NBS on solution quality. Additionally, supply chain costs can be saved by allowing lower fill rates at upstream echelons

A normal approximation model for safety stock optimization in a two-echelon distribution system

This paper presents an approximation model for the retailer replenishment lead-times in a two-echelon distribution system, and discusses its implementation for safety stock optimization in a one-warehouse and N-identical retailers system. The model assumes normality of demand and nominal lead times. It takes into account not only the averages of these parameters but also their variances. This approximation model is first tested on a two-echelon, one-warehouse and N-identical retailers system using discrete event simulation. It is then applied to optimize the safety stock in a two-echelon distribution system of a European market leader in the production and distribution of air conditioning equipment. Results of this implementation are analysed and discussed in detail