Optimal Order Quantity and Inventory Classification Using Clustering

Reshu Agarwal
Additional contact information
Reshu Agarwal: G. L. Bajaj, Department of Computer Science, Greater Noida, India

International Journal of Applied Management Sciences and Engineering (IJAMSE), 2017, vol. 4, issue 2, 41-52

Abstract: Clustering is the process of analyzing data to find clusters of data objects that are similar in some sense to one another. Some research studies have also extended the usage of clustering concept in inventory management. Yet, not many research studies have considered the application of clustering approach on determining both optimal order quantity and loss profit of frequent items. In this paper, ordering policy of frequent items in each cluster is determined and inventory is classified based on loss rule in each cluster. This helps inventory manager to determine optimum order quantity of frequent items together with the most profitable item in each cluster for optimal inventory control. An example is illustrated to validate the results.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJAMSE.2017070104 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jamse0:v:4:y:2017:i:2:p:41-52

Access Statistics for this article

International Journal of Applied Management Sciences and Engineering (IJAMSE) is currently edited by Carolina Machado

More articles in International Journal of Applied Management Sciences and Engineering (IJAMSE) from IGI Global
Bibliographic data for series maintained by Journal Editor ().