Ordering Policy and Inventory Classification Using Temporal Association Rule Mining

A modified framework that applies temporal association rule mining to inventory management is proposed in this article. The ordering policy of frequent items is determined and inventory is classified based on loss rule. This helps inventory managers to determine optimum order quantity of frequent items together with the most profitable item in each time-span. An example is illustrated to validate the results.

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Year of publication:	2018
Authors:	Agarwal, Reshu
Published in:	International Journal of Productivity Management and Assessment Technologies (IJPMAT). - IGI Global, ISSN 2160-9845, ZDB-ID 2703600-5. - Vol. 6.2018, 1 (01.01.), p. 37-49
Publisher:	IGI Global
Subject:	Association Rule Mining \| Cross-Selling \| EOQ \| Inventory Classification \| Inventory Management \| Loss Profit \| Temporal Association Rule Mining

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Type of publication:	Article
Language:	English
Other identifiers:	10.4018/IJPMAT.2018010103 [DOI]
Source:	Other ZBW resources

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