This paper presents a Generalized Nets (GN) model for managing the process of preparing logistical units through outsourcing. Generalized Nets, introduced by Krassimir Atanassov, provide a powerful mathematical and graphical formalism for modeling complex processes, including those with parallel, dynamic, and interconnected components. The developed model describes key stages in the logistics process: processing customer requests, assigning tasks to manufacturers, collecting and arranging supplies in containers, container logistics, document tracking, and customs processing. The GN model represents these processes through transitions, places, and tokens that encapsulate information about system states and executed tasks. This approach enables flexibility in modeling uncertainty, temporal dependencies, and priorities, offering an effective tool for optimizing logistics operations. The proposed model is applicable in automated supply chain management systems, where dynamic adaptation to changing conditions is crucial. The study highlights the advantages of Generalized Nets in logistics and their applicability in enhancing the efficiency and accuracy of processes.