TITLE: The Multiple-Job Repair Kit Problem with Forward Stocking Location Recourse
SPEAKER: Brian Kues
The multiple-job repair kit problem is concerned with choosing which spare parts a traveling technician should carry. The demand for parts at each job is not known until the technician diagnoses the problem on-site. The general objective is to understand and optimize the trade-off between low inventory cost and high customer service level, which is defined as the fraction of jobs completed in a single visit. Hence, jobs which require parts not stocked in the repair kit are considered service failures.
We introduce a new model for a multiple-job repair kit problem where a technician can retrieve needed parts not carried in the repair kit from a forward stocking location in order to complete a job successfully. However, such trips require additional time and hinder the technician’s ability to complete later jobs. This type of spare parts supply chain trades off low inventory cost and high technician productivity. We develop a model for the problem as well as an algorithm to find an inventory policy. We show that the algorithm is not always optimal and can be arbitrarily bad in the worst case but performs well in many computational experiments. We also perform factor screening experiments to examine the sensitivity of the heuristic solutions to the problem parameters.