For the spare parts stocking problem, generally metric type methods are used in the context of capital goods. Implicitly, a decision is assumed on which components to discard and which to repair upon failure, and where to perform repairs. In the military world, this decision is taken explicitly using the level of repair analysis (lora). Since the lora does not consider the availability of the installed base, solving the lora and spare parts stocking problems sequentially may lead to suboptimal solutions. We propose an iterative algorithm to solve the two problems. We compare its performance with that of the sequential approach and a recently proposed, so-called integrated algorithm. The latter finds optimal solutions for two-echelon, single-indenture problems. In our experiment, we use a set of such problems, and a set of multi-echelon, multi-indenture problems, for which we achieve a cost reduction of 3% on average (35% at maximum) compared with the sequential approach. Compared with the integrated algorithm, the gap is only 0.6% on average (5% at maximum), while the maximum computation time falls from 3 hours to 2.5 minutes. In a case study, we achieve a cost reduction of 10% compared with the sequential approach.
|BETA Working papers
|University of Twente, BETA Research School for Operations Management and Logistics
- Spare parts
- Level of repair analysis
- Service Logistics