## 3 Presentation of the Proposed Model
### Sub-Modules of the Presented Model
#### 3.3.6 Product Classification and Allocation Module
Usually, the values of the share are \(X=0.2V_{i}\), \(Y=0.4V_{i}\);  
**Step 7--**Allocation of products to groups: \(X\in(0;0.2];Y\in(0.2;0.4];Z\in(0.4;1]\). As a result of the analysis, the products are divided into XYZ groups, and it is assumed that [12]:  
* The X group consists of products that are used regularly. It should have the monitoring system which is synchronized with the demand. It is not required to create large stocks of goods;
* The Y group is characterized by considerable variability, which makes it difficult to see and use certain patterns, such as seasonality. It is necessary to develop an appropriate level of stockholding;
* The Z group consists of occasional products. It is necessary to choose between creating a stock that will be stored for a long period and on-demand supplies that will require the incurrence of higher expenses. The developed system allows for combining the results provided by XYZ analysis with ABC analysis. The COI Index (cube-per-order index) allows classifying products in the simplest way [13]. This model provides bi-criterion analysis, and the criteria are product size and the demand. The size of the product can be defined by its volume or weight, while the demand by the number of products picked (popularity) or the average demand. The COI Index is calculated as follows (10):  
\[w_{i}\ =\ \frac{v_{i}}{p_{i}};\ i\ =\ 1,2,\ldots,n \tag{10}\]  
By applying the calculated COI Index to distribute products so that the items with the lowest factor are as close to the packaging/delivery area as possible, the path travelled by the largest/heaviest products is shortened. Making a number of goods conditional on the demand allows for striking a balance between these two criteria [30]. The additional advantage of this model is that frequent changes in the order of products on the trolley are avoided, while completing the products within a large weight range and planning the picking process of several orders in one pass from the farthest point to the release zone. Such changes are necessary if there is a risk of damaging the lighter product with the heavier one. Employing the COI Index model indirectly reduces the time required for the product to be transferred, and as a result, reduces the duration of the complete picking. It is possible to use the classic ABC model by double-taking it--once with the weight criterion, and again with the demand for the product criterion. The next step is to determine the weighting factors to compile the results of both analyses. However, with a large assortment, the use of the COI Index will be a much faster method. The COI Index is particularly useful for the free allocation storage method. In most cases, it has an informational and decision-making function and contributes to the reduction of picking time without the need for complex calculations or analyses. The literature on the subject provides information on the use of the COI Indexes to divide products into ABC groups [33]. For this reason, the COI Index model happens to be wrongly associated with ABC analysis. The search algorithm for relationships between products. One of the authors' developed models is the algorithm for determining correlations between products. This is automatic. The application generates a list of pickups according to the configuration settings of the simulation. Consequently, using the author's algorithm, it calculates the number of product appearances in pairs on the pick lists and writes them to the matrix. The last step is to generate a set of potential pick lists with different product appearances. When classifying products, the relationships between them, e.g., the frequency of occurrence on the picking lists, can be used as a criterion for allocation. In such a case, the placement of products is based on the list of products sorted by the greatest number of appearances on the picking lists. Such a solution is not entirely correct as it does not reflect the relationships between the individual products, focusing only on the frequency of their sales.