Distribution and the classical transport model

The virtual company “ECO-Mebel” SA is a furniture manufacturer with two product groups: cabinet furniture sets and upholstered furniture. Depending on the type of furniture, individual segments are produced in a disassembled state or glued together in their entirety at the customer’s request. Therefore, each stage of production ends with acceptance, quality control, and packaging into sets ready for shipment. The company is currently in a growth phase and is recording continuously increasing sales. As of today, the annual sales value is approximately 5.5 million PLN. However, as much as 80% of the value comes from domestic sales. Since it is a relatively young company, all activities related to running the business are based on learning and drawing knowledge from other companies in the industry. Nevertheless, the management is trying to develop its own methods of operation that will allow the company to compete in the market. Furthermore, the company owns its own delivery vehicles, which it uses to distribute furniture to its own furniture showrooms, wholesalers, and main warehouses throughout Poland. Previous solutions regarding transport and customer supply were not optimal. Until now, the distribution territory has been divided taking into account the percentage share of sales in a given region. In each of the created regions, there is a main warehouse from which products are delivered to wholesalers according to demand. Each warehouse is assigned 5 wholesalers, regardless of whether that wholesaler could be supplied from another warehouse due to lower transport costs. In order to optimize transport in terms of costs, distance, and the wholesaler’s demand for a given product, another analysis should be carried out, thanks to which individual wholesalers will be supplied from the warehouses located closest (due to transport costs) and which are able to fulfill the placed order, and not as before from warehouses designated by a partially intuitive division, guided by sales volume.