This study aims to optimize internal logistics processes in manufacturing facilities by analyzing alternative transportation routes and providing optimal solutions. Challenges such as increasing product diversity, complex supply chains, and uncertain demand structures have made the management of logistics processes increasingly critical. By employing vehicle routing methods like Dijkstra’s and k-shortest path algorithms, the study determines optimal transportation routes between facility locations, considering competitive priorities such as cost, quality, delivery speed, and flexibility. In this research, data related to internal logistics processes were analyzed, and a distance matrix was created using the savings algorithm. Based on this matrix, optimal routes were calculated using the k-shortest path algorithm. As part of the application, suitable routes were identified for materials that need to be transported between storage depots, production, and assembly areas within a manufacturing facility. The developed method minimized transportation costs and enhanced flexibility in internal transportation processes. The results demonstrated the effectiveness of collaborative transportation strategies and validated the applicability of the proposed approach through alternative scenario analyses. The study presents a model that serves as a guide not only for the current facility but also for different industries with similar internal logistics processes. It is anticipated that the research will make significant contributions to customer-focused, cost-effective, and flexible logistics management strategies for businesses.