Peer-estimation for multiple criteria ABC inventory classification

Inventory classification is an effective way to manage a large number of items. As a basic methodology, ABC analysis is widely used for classification. The traditional ABC classification is based on only a single criterion. However, it is generally recognized that multiple criteria should be considered in practice. A peer-estimation approach is proposed in this paper for multi-criteria inventory classification (MCIC). The proposed approach determines two common sets of criteria weights and aggregates the resulting two performance scores in the most favorable and least favorable senses for each item without any subjectivity. Comparisons of the proposed approach with some previous methods are illustrated based on a classical MCIC problem. It is shown that our proposed approach can provide a more reasonable and comprehensive performance index for MCIC.