# The Environmental Impact of Inland Empty Container Movements Within Two-Depot Systems
## 6 Conclusions and Future Research  
In this study, we investigated the importance of managing inland movements of empty containers in modern logistics and supply chain operations. This paper proposes a simulation optimization model for the movements of empty containers among a two-depot system and their impact on CO2 emissions, customer waiting times, and system efficiency. ABM successfully captures real-world complexities to simulate the truck movements between the port, inland depots, and customer premises. In this way, the analysis highlights the significant influence of demand frequency and inland depot utilization on network performance. The findings provide several practical implications for logistics managers and policymakers engaged in maritime container transport. According to the simulation, using inland depots can cut greenhouse gas emissions by around 15-25% and help create more stable and effective container circulation by reducing the accumulation of empty containers. These results suggest that inland depots can serve as effective coordination hubs, particularly in heavy-traffic regions or where environmental sustainability is a priority. However, the results also reveal a trade-off between environmental benefits and service efficiency: while depot-based routing supports emission reduction, it may also lead to increased customer waiting times due to added handling activities and longer distances. To address this, decision-makers may consider adopting hybrid routing strategies, where urgent or time-sensitive deliveries follow direct routes, while others are routed  
Figure 6: The average waiting time under different scenarios. through depots to optimize consolidation. Moreover, the reduced variability in empty container flows under the depot scenario highlights the potential of shared depots or container pooling systems to improve equipment utilization and lower operational costs. In practice, companies like Maersk and Hapag-Lloyd are already experimenting with differentiated delivery options and dynamic dispatching technologies to optimize fleet utilization without compromising customer responsiveness. These hybrid strategies, wherein time-sensitive deliveries are routed directly while bulk or lower-priority shipments utilize depot infrastructure, mirror the adaptive approach proposed by this study. From an operational planning perspective, this study demonstrates the value of agent-based modeling as a decision support tool. It enables managers to evaluate different logistics strategies under variable demand and operational constraints before implementation, thereby reducing risk. Furthermore, the model offers a framework for policymakers to assess the impact of routing configurations on emissions, providing a basis for formulating incentives or regulations that encourage more sustainable logistics practices. The proposed ABM was developed to explore the environmental impact of inland empty container movements within a two-depot system. To maintain simplicity, the model includes assumptions such as a closed system, ideal container conditions, and unlimited depot storage. While these help clarify the model's focus, they limit its ability to fully reflect real-world logistics complexities. Additionally, the use of NetLogo as a modeling platform further supports agent-based logic and visualization but presents limitations in terms of computational scalability and performance for large-scale applications. Nevertheless, while ABM is a powerful tool for analyzing complex logistics systems, it has certain limitations. These include high computational requirements for large-scale simulations, reliance on detailed behavioral data, and a lack of standardized frameworks, which can affect model consistency and comparability. Additionally, interpreting emergent behaviours can be challenging without support from complementary analytical methods.