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Evaluation of Machine Learning Algorithms for Predicting the Processing Time of Order Picking in a Warehouse
Tilen Škrinjar, 2019, master's thesis

Abstract: Optimization of warehouse processes increases efficiency and lowers the cost of managing a warehouse. The most expensive and time-consuming activity is picking. Knowing picking process time is an important factor for proper organization of material and information flow. Orders delivered to a packing station too early or too late can cause delays in a warehouse. The purpose of this study is to evaluate machine learning pipeline for processing time prediction of order picking. This includes data gathering, data preprocessing and the evaluation of machine learning algorithms, which are the most important aspects of this research.
Keywords: warehouse, order picking, machine learning, regression analysis
Published: 25.02.2019; Views: 673; Downloads: 0

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