References
Abdul Rahman, N. S. F., Ismail, A., & Lun, V. Y. (2016). Preliminary study on new container stacking/storage system due to space limitations in container yard. Maritime Business Review, 1(1), 21-39. https://doi.org/10.1108/MABR-03-2016-0004
Search via ReFindit
Alessandria, G., Khan, S. Y., Khederlarian, A., Mix, C., & Ruhl, K. J. (2023). The aggregate effects of global and local supply chain disruptions: 2020-2022. Journal of international Economics, 146, 103788. - https://doi.org/10.1016/j.jinteco.2023.103788
Search via ReFindit
Bartosiewicz, A., & Jadczak, R. (2023). Multi-criteria analysis of the competitiveness of major Baltic Sea container terminals. Comparative Economic Research, 26(2), 163-178. https://doi.org/10.18778/1508-2008.26.18
Search via ReFindit
Benghalia, A., Ferdjallah, A., Oudani, M., & Boukachour, J. (2025). Machine Learning and Simulation for Efficiency and Sustainability in Container Terminals. Sustainability, 17(7), 2927. https://doi.org/10.3390/su17072927
Search via ReFindit
Cimino, M. G., Palumbo, F., Vaglini, G., Ferro, E., Celandroni, N., & La Rosa, D. (2017). Evaluating the impact of smart technologies on harbor’s logistics via BPMN modeling and simulation. Information Technology and Management, 18(3), 223-239. https://doi.org/10.1007/s10799-016-0266-4
Search via ReFindit
Cocuzza, E., Ignaccolo, M., Marinacci, C., Ricci, S., Twrdy, E., & Zanne, M. (2025). Sustainable Strategies for Ports and Maritime Logistics: A Methodological Approach to Green Transition. Sustainability, 17(13), 5739. https://doi.org/10.3390/su17135739
Search via ReFindit
Custodio, L., & Machado, R. (2020). Flexible automated warehouse: a literature review and an innovative framework. The International Journal of Advanced Manufacturing Technology, 106, 533-558. https://doi.org/10.1007/s00170-019-04588-z
Search via ReFindit
Eskafi, M., Kowsari, M., Dastgheib, A., Ulfarsson, G. F., Stefansson, G., Taneja, P., & Thorarinsdottir, R. I. (2021). A model for port throughput forecasting using bayesian estimation. Maritime economics and logistics, 23(2), 1-21. https://doi.org/10.1057/S41278-021-00190-X
Search via ReFindit
Farhan, J., & Ong, G. P. (2018). Forecasting seasonal container throughput at international ports using SARIMA models. Maritime Economics & Logistics, 20(1), 131-148. https://doi.org/10.1057/mel.2016.13
Search via ReFindit
Ferrari, E., Christidis, P., & Bolsi, P. (2023). The impact of rising maritime transport costs on international trade: Estimation using a multi-region general equilibrium model. Transportation Research Interdisciplinary Perspectives, 22, 100985. https://doi.org/10.1016/j.trip.2023.100985
Search via ReFindit
Galle, V., Barnhart, C., & Jaillet, P. (2018). Yard crane scheduling for container storage, retrieval, and relocation. European Journal of Operational Research, 271(1), 288-316. https://doi.org/10.1016/j.ejor.2018.05.007
Search via ReFindit
Gattuso, D., & Pellicanò, D. S. (2023). Perspectives for ports development, based on automated container handling technologies. Transportation Research Procedia, 69, 360-367. https://doi.org/10.1016/j.trpro.2023.02.183
Search via ReFindit
Hasan, K. R., Zhang, W., & Shi, W. (2023). A sustainable port-hinterland container transport system: The simulation-based scenarios for CO2 emission reduction. Sustainability, 15(12), 9444. https://doi.org/10.3390/su15129444
Search via ReFindit
Heikkilä, M., Saarni, J., & Saurama, A. (2022). Innovation in Smart Ports: Future Directions of Digitalization in Container Ports. Journal of Marine Science and Engineering, 10(12), 1925. https://doi.org/10.3390/jmse10121925
Search via ReFindit
Hervás-Peralta, M., Poveda-Reyes, S., Molero, G. D., Santarremigia, F. E., & Pastor-Ferrando, J.-P. (2019). Improving the Performance of Dry and Maritime Ports by Increasing Knowledge about the Most Relevant Functionalities of the Terminal Operating System (TOS). Sustainability, 11(6), 1648. https://doi.org/10.3390/su11061648
Search via ReFindit
Hong, C., Guo, Y., Wang, Y., & Li, T. (2023). The Integrated Scheduling Optimization for Container Handling by Using Driverless Electric Truck in Automated Container Terminal. Sustainability, 15(6), 5536. https://doi.org/10.3390/su15065536
Search via ReFindit
Ilesaliev, D. I., Abduvakhitov, S. R., Ismatullaev, A. F., & Makhmatkulov, S. G. (2019). Research of the main storage area of the container terminal. International Journal of Engineering and Advanced Technology (IJEAT), 9(1), 4625-4630. https://doi.org/10.35940/ijeat.A2923.109119
Search via ReFindit
Jobran, Y., & Kara, G. (2022). Examining the Efficiency of Automation in Container Terminals. Journal of Transportation and Logistics, 7(1), 137-155. https://doi.org/10.26650/JTL.2022.1039692
Search via ReFindit
Kamara, T. A. R., Souldan, S. M., Paul, D. J., Smith, D., & Smith, V. (2025). Impact of Infrastructure Investment on Port Efficiency: A Case Study of Queen Elizabeth II Quay, Sierra Leone. Journal of Transportation Technologies, 15(2), 203-221. https://doi.org/10.4236/jtts.2025.152011
Search via ReFindit
Kerbiriou, R. (2024). Modernisation of Container Ship Fleets: State of Play and Consequences for the Baltic Sea. TransNav, The International Journal on Marine Navigation and Safety of Sea Transportation, 18(1), 211-217. https://doi.org/10.12716/1001.18.01.22
Search via ReFindit
Kim, K. H., Lee, K. M., & Hwang, H. (2003). Sequencing delivery and receiving operations for yard cranes in port container terminals. International Journal of Production Economics, 84(3), 283-292. 00466-8 https://doi.org/10.1016/S0925-5273(02)
Search via ReFindit
Kizilay, D., & Eliiyi, D. T. (2021). A comprehensive review of quay crane scheduling, yard operations and integrations thereof in container terminals. Flexible Services and Manufacturing Journal, 33(1), 1-42. https://doi.org/10.1007/s10696-020-09385-5
Search via ReFindit
Lee, H., Lee, J., An, M., Park, G., & Choi, S. (2021). Machine learning approach to analyze the status of forklift vehicles with irregular movement in a shipyard. Computers in Industry, 133, 103544. https://doi.org/10.1016/j.compind.2021.103544
Search via ReFindit
Locaitienė, V., & Čižiūnienė, K. (2024). Assessing the Logistics Efficiency of Baltic Region Seaports Through DEA-BCC and Spatial Analysis. Journal of Marine Science and Engineering, 13(1), 50. https://doi.org/10.3390/jmse13010050
Search via ReFindit
Luo, J., & Wu, Y. (2020). Scheduling of container-handling equipment during the loading process at an automated container terminal. Computers & Industrial Engineering, 149, 106848. https://doi.org/10.1016/j.cie.2020.106848
Search via ReFindit
Mohite, A. A., & Mathew, E. (2025). Exploring the necessary upgrades in port infrastructure to accommodate and support the operation of the next-generation green ships. Marine Systems & Ocean Technology, 20(2), 26. https://doi.org/10.1007/s40868-025-00171-2
Search via ReFindit
Serry, A. (2025). From Crisis to Resilience: The Port of Klaipeda and the Reshaping of Baltic Trade Flows (2014-2023). TransNav: International Journal on Marine Navigation and Safety of Sea Transportation, 19. https://doi.org/10.12716/1001.19.01.16
Search via ReFindit
Stoilova, S. D., & Martinov, S. V. (2019). Choosing the container handling equipment in a rail-road intermodal terminal through multi-criteria methods. In IOP Conference Series: Materials Science and Engineering (Vol. 664, No. 1, p. 012032). IOP Publishing. https://doi.org/10.1088/1757-899X/664/1/012032
Search via ReFindit
Su, Z., Liu, Y., Gao, Y., Park, K.-S., & Su, M. (2024). Critical Success Factors for Green Port Transformation Using Digital Technology. Journal of Marine Science and Engineering, 12(12), 2128. https://doi.org/10.3390/jmse12122128
Search via ReFindit
Tan, C., He, J., & Wang, Y. (2017). Storage yard management based on flexible yard template in container terminal. Advanced Engineering Informatics, 34, 101-113. https://doi.org/10.1016/j.aei.2017.10.003
Search via ReFindit
Tang, P., Postolache, O. A., Hao, Y., & Zhong, M. (2019). Reefer container monitoring system. In 2019 11th International Symposium on Advanced Topics in Electrical Engineering (ATEE) (pp. 1-6). IEEE. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8724950&casa_token=mqt3kpUhdFUAAAAA:PxA3Usxt7fk7HybXCyqyS-oOOctlFGIrAubCOIKrfA7AxGXMq-3GwaKuYnjPibKj44Cz-a-ioc4y
Search via ReFindit
Tran, N. K., & Lam, J. S. L. (2024). CO2 emissions in a global container shipping network and policy implications. Maritime Economics & Logistics, 26(1), 151-167. https://doi.org/10.1057/s41278-022-00242-w
Search via ReFindit
Tran, N. K., Haralambides, H., Notteboom, T., & Cullinane, K. (2025). The costs of maritime supply chain disruptions: The case of the Suez Canal blockage by the ‘Ever Given’ megaship. International Journal of Production Economics, 279, 109464. https://doi.org/10.1016/j.ijpe.2024.109464
Search via ReFindit
Tsolakis, N., Zissis, D., Papaefthimiou, S., & Korfiatis, N. (2022). Towards AI driven environmental sustainability: an application of automated logistics in container port terminals. International Journal of Production Research, 60(14), 4508-4528. https://doi.org/10.1080/00207543.2021.1914355
Search via ReFindit
Vis, I. F., de Koster, R. M. B., & Savelsbergh, M. W. (2005). Minimum vehicle fleet size under time-window constraints at a container terminal. Transportation Science, 39(2), 249-260. https://doi.org/10.1287/trsc.1030.0063
Search via ReFindit
Vrbová, P., Cempírek, V., Stopková, M., & Bartuška, L. (2018). Various electronic data interchange (EDI) usage options and possible substitution. NAŠE MORE: znanstveni časopis za more i pomorstvo, 65(4 Special issue), 187-191. https://doi.org/10.17818/NM/2018/4SI.4
Search via ReFindit
Wan, Z., Su, Y., Li, Z., Zhang, X., Zhang, Q., & Chen, J. (2023). Analysis of the impact of Suez Canal blockage on the global shipping network. Ocean & Coastal Management, 245, 106868. https://doi.org/10.1016/j.ocecoaman.2023.106868
Search via ReFindit
Weerasinghe, B. A., Perera, H. N., & Bai, X. (2024). Optimizing container terminal operations: a systematic review of operations research applications. Maritime Economics & Logistics, 26(2), 307-341. https://doi.org/10.1057/s41278-023-00254-0
Search via ReFindit
Wu, W., & Gao, S. (2023). Port container throughput prediction method based on SSA-SVM. Highlights in Business, Economics and Management, 12 null, 88-95. https://doi.org/10.54097/hbem.v12i.8326
Search via ReFindit
Yavuz, H., & Beller, S. (2021). An intelligent serial connected hybrid control method for gantry cranes. Mechanical Systems and Signal Processing, 146, 107011. https://doi.org/10.1016/j.ymssp.2020.107011
Search via ReFindit
Zhang, H., Di, X., & Yang, L. (2023, June). An improvement of Pearson correlation coefficient for variable importance analysis. In 2023 8th International Conference on Computational Intelligence and Applications (ICCIA) (pp. 83-90). IEEE. https://doi.org/10.1109/iccia59741.2023.00023
Search via ReFindit
Zhang, Q., Dong, H., Ling, M., Duan, L., & Wei, Y. (2020). Optimization of gantry cranes’ operation path for transshipment based on improved TSP. Journal of Advanced Transportation, 2020(1), 9861370. https://doi.org/10.1155/2020/9861370
Search via ReFindit
Zhuang, X., Li, W., & Xu, Y. (2022). Port Planning and Sustainable Development Based on Prediction Modelling of Port Throughput: A Case Study of the Deep-Water Dongjiakou Port. Sustainability, 14(7), 4276. https://doi.org/10.3390/su14074276
Search via ReFindit
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