Determining Optimal Parameters for Expediting Policies

We consider an inventory policy that expedites delivery times of open orders if the inventory level drops below a certain threshold. By expediting open orders, back orders can be reduced. Order expediting is costly, and we include various types of expediting costs in the model. We prove structural properties of the model and show how the optimal parameters of the expediting policy can be computed efficiently. The expediting policy is easy to implement and, for situations with variable expediting cost only, the structure of the policy is optimal. For situations with nonvariable expediting costs, the expediting policy that we consider is generally not optimal. The optimal policy can be computed by dynamic programming, but this approach is computationally feasible only for small-problem instances. We conduct numerical experiments that are based on data from the service division of a global equipment manufacturer to evaluate the performances of the expediting policy and the optimal policy. The results show that substantial cost savings can be achieved by order expediting and that the expediting policy realizes a great share of the cost-saving potential offered by order expediting

Determining optimal parameters for expediting policies under service level constraints

Order expediting is an inventory control practice that allows companies to reduce inventory while maintaining service levels. However, expediting outstanding orders is costly and a trade-off must be made between expediting orders and holding inventory. We model the problem as a periodic-review inventory system with the option to move outstanding units forward in the replenishment pipeline. The objective is to minimize the sum of expected inventory holding and expediting costs per period subject to a minimum expected service level constraint. We consider a generalized base-stock policy where outstanding units are expedited when the inventory level drops below a certain threshold. We develop structural properties and present an efficient procedure to determine the optimal policy parameters. In a numerical study with real-world data, we show that our expediting policy offers substantial savings compared to other policies. We also provide managerial insights by numerically analyzing how the model parameters impact the savings. (C) 2019 Elsevier B.V. All rights reserved