EOQ Model With Imperfect Items and Backorder with Allowable Proportionate Discount using Cross Selling Effects
Bhawani Sankar Panigrahi1, Sanjay Kumar2, Pabitra Kumar Tripathy3

1Bhawani Sankar Panigrahi, Research Scholar, Kalinga University, Naya Raipur (Chhattisgarh), India.
2Dr. Sanjay Kumar, Associate Professor, Kalinga University, Chhattisgarh Naya Raipur (Chhattisgarh), India.
3Dr. Pabitra Kumar Tripathy, Associate Professor, Department of Computer Science and Engineering, Kalam Institute of Technology, Berhampur, (Odisha), India.
Manuscript received on 03 March 2023 | Revised Manuscript received on 17 March 2023 | Manuscript Accepted on 15 April 2023 | Manuscript published on 30 April 2023 | PP: 18-24 | Volume-12 Issue-5, April 2023 | Retrieval Number: 100.1/ijitee.E94850412523 | DOI: 10.35940/ijitee.E9485.0412523

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Abstract: The primary objective of this idea is to create an EOQ model for imperfectly-quality products that takes into account the combined effects of proportionate discount, backorder, clustering with association rule mining, and cross-selling. The ordering policy considering the cross-selling effect was first calculated in this paper. The benefits of cross-selling become especially evident when selling low-quality products. Data mining methods of varying sophistication are used to determine the nature of the connections between the objects. Clustering is used to group together items in the inventory database that are likely to be used together, and then the Apriori algorithm is used to build common item sets from inside each cluster. By the use of cross-selling, the most frequently purchased items are treated as unique entities. In addition, the EOQ of these entities is determined alongside the deficit threshold. Finally, a numerical example is taken into account to verify the results of the suggested work.
Keywords: EOQ, Backorder, Imperfect, Discount, Selling Effects, Cross-Selling
Scope of the Article: Artificial Intelligence and Machine Learning