Industrial management
Mohsen Kochaki; Behnam Vahdani
Abstract
The correct storage and arrangement of products in the warehouse increases the efficiency in responding to requests, accelerates the identification of products, increases the accessibility of the items in the warehouse, makes more use of the available space in the warehouse, determines the position of ...
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The correct storage and arrangement of products in the warehouse increases the efficiency in responding to requests, accelerates the identification of products, increases the accessibility of the items in the warehouse, makes more use of the available space in the warehouse, determines the position of the products in the warehouse and does not damage it. maximum flexibility and optimal storage conditions are provided. By examining the studies that have been conducted in the field of warehousing and arrangement of products in the warehouse, and before arranging the products in the warehouse, comprehensively and comprehensively, according to the characteristics of the goods, they have not been categorized. Therefore, in this article, by using machine learning algorithms and data mining, according to the characteristics that are considered for the goods in the warehouse of Farasan industrial-production factory, the products are categorized and then the products are arranged in the warehouse using We have paid mathematical programming model. The purpose of the investigated problem in the field of warehousing and arrangement of products, in addition to categorizing products based on their characteristics, is to minimize the cost function obtained in relation to the mathematical planning model. Therefore, for the category Classification of goods is done using density-based algorithm (DB), self-organizing mapping neural network (SOM) and hierarchical clustering method (AGNES). The obtained results show that the SOM network has a better performance than the density-based algorithm and also the density-based algorithm has a better performance than the hierarchical clustering method.
