Selecting Appropriate Type of Package with Machine Learning Models in Logistic Companies

Yasin Can Kılıçkap, Berk AYVAZ


There are many factors for Logistics Companies to be successful and financially profitable. These factors can be grouped under two main headings, namely, the efficiency values of the processes and the costs. One of the most important costs is the cost of packaging and shifting. When the packaged orders are delivered to the cargo companies, the packaging and shifting costs are incurred in a way that is directly proportional to the volume value of the order. In logistics companies, these costs increase as a result of placing the order in a package with a larger volume value instead of the appropriate package type. Solving the pallet loading or container loading problems with mathematical models, the packaging personnel's output of the mathematical model for each order, and the employee's placing these products in the package according to the results of the model significantly reduce the efficiency value of the processes. For this reason, in this article, it is aimed to examine and learn the historical packaging data with different machine learning models and to inform the packaging personnel about which package type should be used for the current order.


Container Loading Problem; Logistic Companies; Machine Learning; Packaging; Pallet Loading Problem

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ISSN 2233 -1859

Digital Object Identifier DOI: 10.21533/scjournal

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