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http://repository.kln.ac.lk/handle/123456789/25432
Title: | An Effective Lateral Transhipment Model for A Multi-Location Inventory Setting to Minimize |
Authors: | Kumari, A.G.K.C. Wijayanayake, A. N. Niwunhella, D. H. H. |
Keywords: | inventory management, lateral transhipment, proactive transhipment, retail industry |
Issue Date: | 2022 |
Publisher: | Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka |
Citation: | Kumari A.G.K.C.; Wijayanayake A. N.; Niwunhella D. H. H. (2022), An Effective Lateral Transhipment Model for A Multi-Location Inventory Setting to Minimize, International Research Conference on Smart Computing and Systems Engineering (SCSE 2022), Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka. 225-230. |
Abstract: | Managing inventory levels to ensure on-shelf availability of products is a challenge that retailers face on a daily basis. Even though it is desirable to have additional inventory to ensure the availability of products, it increases the inventory holding cost. Hence, retailers use lateral transhipment as a method to redistribute inventory from a location which has excess inventory to another outlet which faces / will face stockouts. This paper proposes a mathematical model to minimize the total cost through proactive lateral transhipment while reducing the stockouts, significantly. A multi-item, multi-location inventory system was considered, and a cost minimization model was developed based on the tradeoff between the potential gain and the transhipment cost. The model was implemented using Python programming language and validated using a real-world data set from one of the leading supermarket chains. The results from the model have shown that it can reduce the total cost and stockout occurrences significantly. |
URI: | http://repository.kln.ac.lk/handle/123456789/25432 |
Appears in Collections: | Smart Computing and Systems Engineering - 2022 (SCSE 2022) |
Files in This Item:
File | Description | Size | Format | |
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SCSE 2022 34.pdf | 115.6 kB | Adobe PDF | View/Open |
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