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https://doi.org/10.24867/symop...
Article . 2024 . Peer-reviewed
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OPTIMIZING INVENTORY CLASSIFICATION: A MULTI-CRITERIA APPROACH BASED ON ORDINAL SUMS OF CONJUNCTIVE AND DISJUNCTIVE FUNCTIONS

Authors: Anđelić, Ognjen; Milošević, Pavle; Rakićević, Zoran; Hudec, Miroslav; Barčáková, Nina;

OPTIMIZING INVENTORY CLASSIFICATION: A MULTI-CRITERIA APPROACH BASED ON ORDINAL SUMS OF CONJUNCTIVE AND DISJUNCTIVE FUNCTIONS

Abstract

Inventory management plays a significant role in manufacturing organizations as it balances supply and demand, i.e. ensures the continuity of production, the satisfaction of customer demand and the minimization of costs inventory level optimization. Efficient inventory management highly depends on the categorization of inventory items to simplify the management process and decide on an appropriate inventory management policy. In this paper, two different methods are used to classify 290 inventory items with the aim of examining the differences between them. The first method is the classical single-criteria ABC analysis based on consumption value, while the second is a multi-criteria ABC classification based on ordinal sums. Both classification methods categorize items into three classes, A, B and C, based on their importance. Although both classification methods have a relatively high agreement rate (73.84%), a third of all misclassification cases are cases that could lead inventory managers to neglect the items of the highest importance. Therefore, it is recommended to pay special attention to these items and make a timely decision on an appropriate inventory management policy for them. Finally, this article discusses topics for the future improvements of this first attempt to apply ordinal sums in this field.

Keywords

Inventory management and classification, ABC analysis, multi-criteria approach, ordinal sums of conjunctive and disjunctive functions

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green