-Aznam, N. H. Z., & Khurizan, N. (2023). Discrete-Event Simulation and Data Envelopment Analysis in Port Efficiency Evaluation: A Bibliometric Analysis and Mapping of Combined Databases. In Proceedings of the 3rd International Conference on Advanced Information Scientific Development (ICAISD 2023), SciTePress. Vol. 1, 84–95.doi.org/10.5220/0012444300003848
-Bett, D. K., Ali, I., Gheith, M., & Eltawil, A. (2024). Simulation-Based Optimization of Truck Appointment Systems in Container Terminals: A Dual Transactions Approach with Improved Congestion Factor Representation. Logistics, 8(3), 80.
-Fiori, C., Cisternas, L. J., & de Luca, S. (2025). A discrete-event multi-agent simulation framework supporting well-to-wheel analysis for greening commercial maritime ports. Simulation Modelling Practice and Theory, 140, 103061.
-Gross, D., Shortle, J. F., Thompson, J. M., & Harris, C. M. (2008). Fundamentals of queueing theory (4th ed.). Wiley.
-Kuo, T.-C., Huang, W.-C., Wu, S.-C., & Cheng, P.-L. (2006). A case study of inter-arrival time distributions of container ships. Journal of Marine Science and Technology, 14(3), 161-166.
-Luo, Q., Song, P., & Zhou, Y. (2024). An improved equilibrium optimizer for solving multi-quay berth allocation problem. International Journal of Computational Intelligence Systems, 17, 177. doi.org/10.1007/s44196-024-00585-7
-Min, H., & Park, B.-I. (2008). Hybrid data envelopment analysis and simulation methodology for measuring capacity utilisation and throughput efficiency of container terminals. Management Faculty Publications, 3. Bowling Green State University.
-Park, K., Kim, M., & Bae, H. (2024). A predictive discrete event simulation for predicting operation times in container terminal. IEEE Access, 12, 10.1109/ACCESS.2024.3389961. doi.org/10.1109/ACCESS.2024.3389961
-Petering, M. and Murty, K. (2009). Effect of block length and yard crane deployment systems on overall performance at a seaport container transshipment terminal. Computers and Operations Research, 36:1711–1725.
-Sislioglu, M., Celik, M., & Ozkaynak, S. (2019). A simulation model proposal to improve the productivity of container terminal operations through investment alternatives. Maritime Policy & Management, 46(2),
156–177. doi.org/10.1080/03088839.2018.1489165
-Steenken, D., Voß, S., & Stahlbock, R. (2004). Container terminal operation and operations research – a classification and literature review. OR Spectrum, 26, (1), 3–49.
-Sun, S., Shi, X., & Zheng, D. (2025). Enhancing the truck appointment system at container terminals based on data-driven and intelligent decision-making methods. International Journal of Systems Science: Operations & Logistics, 12(1). doi.org/10.1080/23302674.2025.2518463
-Yu, J., Tang, G., Song, X., Yu, X., Qi, Y., Li, D., & Zhang, Y. (2018). Ship arrival prediction and its value on daily container terminal operation. Ocean Engineering, 157, 73–86.
-Zehendner, E., & Feillet, D. (2014). Benefits of a truck appointment system on the service quality of inland transport modes at a multimodal container terminal. European Journal of Operational Research, 235(2),
461–469