tailieunhanh - A note on multi criteria inventory classification using weighted linear optimization

In this paper, we produce the correct results and compare them to the original results and those of the extended models. We also improve this model to rank items with an optimal score of 1 using a cross-efficiency technique. The classification results are considerably different from the original results. | Yugoslav Journal of Operations Research Volume 20 (2010), Number 2, 293-299 DOI: A NOTE ON MULTI-CRITERIA INVENTORY CLASSIFICATION USING WEIGHTED LINEAR OPTIMIZATION Jafar REZAEI Section Technology, Strategy and Entrepreneurship, Faculty of Technology, Policy and Management, Delft University of Technology, . Box 5015, 2600 GA Delft, The Netherlands Received: May 2009 / Accepted: November 2010 Abstract: Recently, Ramanathan (R., Ramanathan, ABC inventory classification with multiple-criteria using weighted linear optimization, Computer and Operations Research, 33(3) (2006) 695-700) introduced a simple DEA-like model to classify inventory items on the basis of multiple criteria. However, the classification results produced by Ramanathan are not consistent with the domination concept encouraged some researchers to extend his model. In this paper, we produce the correct results and compare them to the original results and those of the extended models. We also improve this model to rank items with an optimal score of 1 using a cross-efficiency technique. The classification results are considerably different from the original results. Despite the fact that the correct results are obtained in this paper, there is no significant difference between the original model and its extensions, while the original model is more simple and suitable for the situations in which decision-maker cannot assign specific weights to individual criteria. Keywords: Inventory classification, weighted linear optimization, multi-criteria decision-making. AMS Subject Classification: 90B05, 90B05. 1. INTRODUCTION Most organizations classify their inventory items into three classes: A - very important, B - of average importance, and C - relatively unimportant. The more important the inventory item, the greater the level of attention and control it receives. While the traditional classification approach defines the importance of inventory items in terms .

• Kinh tế học
• Inventory classification
• Weighted linear optimization
• Multi criteria decision making
• Extended models
• Cross efficiency technique