Sensitive Analysis of the ZF Model for ABC Multi Criteria Inventory Classification

ABC classification is widely used by managers for inventory control. The classical ABC classification is based on Pareto principle and according to the criterion of the annual use value only. Single criterion classification is often insufficient for a closely inventory control. Multi-criteria inventory classification models have been proposed by researchers in order to consider other important criteria. From these models, we will consider a specific model in order to make a sensitive analysis on the composite score calculated for each item. In fact, this score, based on a normalized average between a good and a bad optimized index, can affect the ABC-item classification. We will focus on items differently assigned to classes and then propose a classification compromise.

Authors:

• Makram Ben Jeddou

Keywords:

• ABC classification
• Multi criteria inventory classification models
• ZF-model.

References:

[1] A.Kontis, and V.Vrysagotis, “A literature review of multi-criteria
approaches based on DEA,” Advances in Mangement and Applied
Economics, vol.1 no.2, pp 207–219, 2011.
[2] R.Ramanathan, “ABC inventory classification with multiple-criteria
using weighted linear optimization,” Computers and Operations
Research, no.33, pp 695–700, 2006.
[3] P.Zhou & L.Fan, “A note on multi-criteria ABC inventory classification
using weighted linear optimization,” European Journal of Operational
Research, no.182, pp 1488–1491, 2007.
[4] L.W. Ng, “A simple classifier for multiple criteria ABC analysis,”
European Journal of Operational Research, no.177, pp 344–353, 2007.
[5] A. Hadi-Vencheh, “An improvement to multiple criteria ABC inventory
classification,” European Journal of Operational Research, no.201, pp
962–965, 2010.
[6] J.Chen, “Peer-estimation for multiple criteria ABC inventory
classification,” Computers and Operations Research, no.38, pp 1784–
1791, 2011.
[7] BE.Flores, D.L. Olson, V.K. Dorai, “Management of multi-criteria
classification,” Mathematical and Computer modelling, no.16, pp 71–
82, 1992.