## 4 Implementation of the Presented Model as Simulation Software  
The proposed model was used as a base algorithm for implementation in the authors' own software called Pickup Simulo. The system was coded in PHP language and MySQL relational databases, and has been tested for code integrity and standards compliance. Besides, each of the developed algorithms were tested on examples, which were then manually calculated to detect logical and algorithmic errors. These types of errors would not be impossible to detect with only code validation. After a thorough examination of many different cases, errors in the application were excluded. Thus, the impact of the application on simulation results was excluded, which was extremely important from a research pointof view. The design of algorithms and coding took ten months. Another four were dedicated to the validation of the application and the improvement of the identified errors. Thanks to the proposed model it is possible to use large batches of data, clearly display the results and easily modify input parameters. The developed application allows its integration with MatLab. The developed system based on the presented model enables the following:  
* presentation of the warehouse structure in a mathematical form;
* description of parameters of products stored in the warehouse;
* classification of products using the methods ABC, XYZ analysis and COI Index, and such criteria as product popularity, number of items sold, weight or volume;
* simulation of the allocation of products in the warehouse;
* creating a sample order-picking list;
* simulation of the order-picking process. The application allows the performing of any number of simulations so that you can get a large set of results. In addition, the information provided is a good set of research data, which consist of the following:  
* order-picking lists associated with product parameters (weight, volume, popularity, number of shelf units occupied);
* recording the distribution of products in the warehouse;
* accessing time for each product in the storage rack;
* order-picking time;
* statistical information for each order-picking, such as the order of products taken, the total volume and weight of products, the number of assortment items on the picking list and the number of pieces taken. The first application module is a data preparation module that allows configuring the shelves, in terms of rack dimensions (Figure 7), as well as the warehouse structure (Figure 8). After entering data in the system, one can proceed to the next step of creating the warehouse structure. This part of the module is automated, based on the warehouse configuration. The program itself creates a matrix (\(W\)) corresponding to the storage locations (shelves) and corridors. In this step, the access times for the individual storage areas in the warehouse are calculated. Figure 7: Pickup Simulo, shelves\({}^{\prime}\) rack dimensions configuration screen. The next module is the classification and simulation module, consisting of three stages--the classification of products, the planning of their allocation in the warehouse and the simulation of order-picking. At the stage of product classification, one of the classification methods should be selected from the following:  
* the association search algorithm;
* ABC analysis combined with XYZ analysis;
* ABC analysis, modification of ABC analysis with dynamic boundary-setting combined with COI Index. For the last two methods, an analysis criterion should be specified--product popularity, number of items sold, as well as weight or volume. In the case of the association search algorithm and XYZ analysis, the criteria are determined automatically. Moreover, for the ABC analysis, it is possible to additionally take the COI Index into account. The last option of this module is to simulate the order-picking. The first step is to set the simulation parameters.