Evaluating discriminating power of single-criteria and multi-criteria models towards inventory classification

- Single-criteria and various multi-criteria models are compared.
- Models are tested for their ability to classify inventory.
- Discriminating power test is introduced.
- Drawback of using single-criteria and R model is captured.
- Effectiveness of using criteria in descending order is highlighted.

Single-criteria and multi-criteria models both are used with regards to inventory classification. In this paper, we evaluated single-criteria and multi-criteria models in terms of their feasibility in classifying inventory items for a given dataset. We introduced discriminating power test. We used two datasets with lead time as the first criterion. We compared the scores of the models. We also modified ZF model and used descending ranking order criteria constraint to address the infeasibilities. Results show that using criteria in descending order reduces the classification infeasibility. Later, we proposed a probability distribution to find the probability of infeasibility for a given dataset against a number of identical scoring items.