Allocating service parts in two-echelon networks at a utility company

A model for the optimal allocation of service parts in a two-echelon network under an aggregate waiting time constraint is developed and simple classification rules are derived from the solution of the multi-item, two-EChelon service part optimization problem using statistical techniques.

Abstract

We study a multi-item, two-echelon, continuous-review inventory problem at a Dutch utility company. We develop a model for the optimal allocation of service parts in a two-echelon network under an aggregate waiting time constraint. Specific model aspects are emergency shipments in case of stockout, and batching for regular replenishment orders at the central warehouse. We use column generation to solve this problem with various building blocks for single-item models as columns. Further, we derive simple classification rules from the solution of our multi-item, two-echelon service part optimization problem using statistical techniques. Application of our models at Liander yields a cost reduction of 15% and a decrease in the impact of waiting time for service parts by 52%.