How to cite this paper
Ighravwe, D., AIkhuele, D., Fayomi, O & Basil, A. (2022). Adoption of a multi-criteria approach for the selection of operational measures in a maritime environment.Journal of Project Management, 7(1), 53-64.
Refrences
Abou Kasm, O., Diabat, A., & Cheng, T. C. E. (2019). The integrated berth allocation, quay crane assignment and scheduling problem: mathematical formulations and a case study. Annals of Operations Research, 1–27.
Agarwal, R., & Ergun, Ö. (2008). Ship scheduling and network design for cargo routing in liner shipping. Transporta-tion Science, 42(2), 175–196.
Aguilar-Chinea, R. M., Rodriguez, I. C., Expósito, C., Melian-Batista, B., & Moreno-Vega, J. M. (2019). Using a deci-sion tree algorithm to predict the robustness of a transshipment schedule. Procedia Computer Science, 149, 529–536.
Ambrosino, D., Bramardi, A., Pucciano, M., Sacone, S., & Siri, S. (2011). Modeling and solving the train load planning problem in seaport container terminals. 2011 IEEE International Conference on Automation Science and Engineer-ing, 208–213.
Euchi, J., Moussi, R., Ndiaye, F., & Yassine, A. (2016). Ant colony optimisation for solving the container stacking prob-lem: Case of le Havre (France) seaport terminal. International Journal of Applied Logistics (IJAL), 6(2), 81–101.
Fang, S., Wang, Y., Gou, B., & Xu, Y. (2019). Toward Future Green Maritime Transportation: An Overview of Seaport Microgrids and All-Electric Ships. IEEE Transactions on Vehicular Technology, 69(1), 207–219.
Gong, Z., & Liu, N. (2020). Mitigative and adaptive investments for natural disasters and labor strikes in a seaport--dry port inland logistics network. Maritime Policy & Management, 47(1), 92–108.
Guenther, H.-O., Grunow, M., Lehmann, M., Neuhaus, U., & Yilmaz, I. O. (2006). Simulation of transportation activi-ties in automated seaport container terminals. Second International Intelligent Logistics System Conference.
Ighravwe, D., & Anyaeche, C. (2019). A comparison of ARIMA and ANN techniques in predicting port productivity and berth effectiveness. International Journal of Data and Network Science, 3(1), 13–22.
Iris, Ç., Pacino, D., Ropke, S., & Larsen, A. (2015). Integrated berth allocation and quay crane assignment problem: Set partitioning models and computational results. Transportation Research Part E: Logistics and Transportation Re-view, 81, 75–97.
Li, S., & Jia, S. (2019). The seaport traffic scheduling problem: Formulations and a column-row generation algorithm. Transportation Research Part B: Methodological, 128, 158–184.
Meersman, H., de Voorde, E., & Vanelslander, T. (2012). Port congestion and implications to maritime logistics. Mari-time Logistics: Contemporary Issues, 49–68.
Mi, Y. (2016). Robust liner shipping schedule design in service networks with transshipment cut and run decisions.
Moussi, R., Euchi, J., Yassine, A., & Ndiaye, N. F. (2015). A hybrid ant colony and simulated annealing algorithm to solve the container stacking problem at seaport terminal. International Journal of Operational Research, 24(4), 399–422.
Na, L., & Zhihong, J. (2009). Optimisation of continuous berth and quay crane allocation problem in seaport container terminal. 2009 Second International Conference on Intelligent Computation Technology and Automation, 3, 229–233.
Rekik, I., & Elkosantini, S. (2019). A multi agent system for the online container stacking in seaport terminals. Journal of Computational Science, 35, 12–24.
Rekik, I., Elkosantini, S., & Chabchoub, H. (2017). A case based reasoning based multi-agent system for the reactive container stacking in seaport terminals. Procedia Computer Science, 108, 927–936.
Shemshadi, A., Shirazi, H., Toreihi, M., & Tarokh, M. J. (2011). A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Systems with Applications, 38(10), 12160–12167.
Song, L., Cherrett, T., & Guan, W. (2012). Study on berth planning problem in a container seaport: Using an integrated programming approach. Computers & Industrial Engineering, 62(1), 119–128.
Steenken Dirk, S. V., & Stahlbock, R. (2004). Container terminal operation and operations research-a classification and literature review. OR Spectrum, 26(1), 3–49.
Ulutaş, A., Karakuş, C. B., & Ayşe, T. (2020). Location selection for logistics center with fuzzy SWARA and cocoso methods. Journal of Intelligent & Fuzzy Systems, Preprint, 1–17.
Vale, J., Ribeiro, J.A., & Branco, M. (2017). Intellectual capital management and power mobilisation in a seaport.
Vasileva, O, & Kiyaev, V. (2018). Monitoring and controlling the execution of the sea cargo port operation's schedule based on multi-agent technologies. CEUR Workshop Proceedings of the 2nd International Scientific and Practical Conference "Fuzzy Technologies in the Industry--FTI, 2258, 243–248.
Vasileva, Olga, & Kiyaev, V. (2018). Generation of efficient cargo operation schedule at seaport with the use of multi-agent technologies and genetic algorithms. International Conference on Intelligent Information Technologies for In-dustry, 401–409.
Wang, R., Nguyen, T. T., Li, C., Jenkinson, I., Yang, Z., & Kavakeb, S. (2019). Optimising discrete dynamic berth allo-cations in seaports using a Levy Flight based meta-heuristic. Swarm and Evolutionary Computation, 44, 1003–1017.
Wang, T.-C., & Lee, H.-D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980–8985.
Wright, S. L., Thompson, R. C., & Galloway, T. S. (2013). The physical impacts of microplastics on marine organisms: a review. Environmental Pollution, 178, 483–492.
Yan, B., Jin, J. G., Zhu, X., Lee, D.-H., Wang, L., & Wang, H. (2020). Integrated planning of train schedule template and container transshipment operation in seaport railway terminals. Transportation Research Part E: Logistics and Transportation Review, 142, 102061.
Yan, B., Zhu, X., Lee, D.-H., Jin, J. G., & Wang, L. (2020). Transshipment operations optimisation of sea-rail intermod-al container in seaport rail terminals. Computers & Industrial Engineering, 141, 106296.
Yang, Z., Ng, A. K. Y., & Wang, J. (2014). A new risk quantification approach in port facility security assessment. Transportation Research Part A: Policy and Practice, 59, 72–90.
Agarwal, R., & Ergun, Ö. (2008). Ship scheduling and network design for cargo routing in liner shipping. Transporta-tion Science, 42(2), 175–196.
Aguilar-Chinea, R. M., Rodriguez, I. C., Expósito, C., Melian-Batista, B., & Moreno-Vega, J. M. (2019). Using a deci-sion tree algorithm to predict the robustness of a transshipment schedule. Procedia Computer Science, 149, 529–536.
Ambrosino, D., Bramardi, A., Pucciano, M., Sacone, S., & Siri, S. (2011). Modeling and solving the train load planning problem in seaport container terminals. 2011 IEEE International Conference on Automation Science and Engineer-ing, 208–213.
Euchi, J., Moussi, R., Ndiaye, F., & Yassine, A. (2016). Ant colony optimisation for solving the container stacking prob-lem: Case of le Havre (France) seaport terminal. International Journal of Applied Logistics (IJAL), 6(2), 81–101.
Fang, S., Wang, Y., Gou, B., & Xu, Y. (2019). Toward Future Green Maritime Transportation: An Overview of Seaport Microgrids and All-Electric Ships. IEEE Transactions on Vehicular Technology, 69(1), 207–219.
Gong, Z., & Liu, N. (2020). Mitigative and adaptive investments for natural disasters and labor strikes in a seaport--dry port inland logistics network. Maritime Policy & Management, 47(1), 92–108.
Guenther, H.-O., Grunow, M., Lehmann, M., Neuhaus, U., & Yilmaz, I. O. (2006). Simulation of transportation activi-ties in automated seaport container terminals. Second International Intelligent Logistics System Conference.
Ighravwe, D., & Anyaeche, C. (2019). A comparison of ARIMA and ANN techniques in predicting port productivity and berth effectiveness. International Journal of Data and Network Science, 3(1), 13–22.
Iris, Ç., Pacino, D., Ropke, S., & Larsen, A. (2015). Integrated berth allocation and quay crane assignment problem: Set partitioning models and computational results. Transportation Research Part E: Logistics and Transportation Re-view, 81, 75–97.
Li, S., & Jia, S. (2019). The seaport traffic scheduling problem: Formulations and a column-row generation algorithm. Transportation Research Part B: Methodological, 128, 158–184.
Meersman, H., de Voorde, E., & Vanelslander, T. (2012). Port congestion and implications to maritime logistics. Mari-time Logistics: Contemporary Issues, 49–68.
Mi, Y. (2016). Robust liner shipping schedule design in service networks with transshipment cut and run decisions.
Moussi, R., Euchi, J., Yassine, A., & Ndiaye, N. F. (2015). A hybrid ant colony and simulated annealing algorithm to solve the container stacking problem at seaport terminal. International Journal of Operational Research, 24(4), 399–422.
Na, L., & Zhihong, J. (2009). Optimisation of continuous berth and quay crane allocation problem in seaport container terminal. 2009 Second International Conference on Intelligent Computation Technology and Automation, 3, 229–233.
Rekik, I., & Elkosantini, S. (2019). A multi agent system for the online container stacking in seaport terminals. Journal of Computational Science, 35, 12–24.
Rekik, I., Elkosantini, S., & Chabchoub, H. (2017). A case based reasoning based multi-agent system for the reactive container stacking in seaport terminals. Procedia Computer Science, 108, 927–936.
Shemshadi, A., Shirazi, H., Toreihi, M., & Tarokh, M. J. (2011). A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Systems with Applications, 38(10), 12160–12167.
Song, L., Cherrett, T., & Guan, W. (2012). Study on berth planning problem in a container seaport: Using an integrated programming approach. Computers & Industrial Engineering, 62(1), 119–128.
Steenken Dirk, S. V., & Stahlbock, R. (2004). Container terminal operation and operations research-a classification and literature review. OR Spectrum, 26(1), 3–49.
Ulutaş, A., Karakuş, C. B., & Ayşe, T. (2020). Location selection for logistics center with fuzzy SWARA and cocoso methods. Journal of Intelligent & Fuzzy Systems, Preprint, 1–17.
Vale, J., Ribeiro, J.A., & Branco, M. (2017). Intellectual capital management and power mobilisation in a seaport.
Vasileva, O, & Kiyaev, V. (2018). Monitoring and controlling the execution of the sea cargo port operation's schedule based on multi-agent technologies. CEUR Workshop Proceedings of the 2nd International Scientific and Practical Conference "Fuzzy Technologies in the Industry--FTI, 2258, 243–248.
Vasileva, Olga, & Kiyaev, V. (2018). Generation of efficient cargo operation schedule at seaport with the use of multi-agent technologies and genetic algorithms. International Conference on Intelligent Information Technologies for In-dustry, 401–409.
Wang, R., Nguyen, T. T., Li, C., Jenkinson, I., Yang, Z., & Kavakeb, S. (2019). Optimising discrete dynamic berth allo-cations in seaports using a Levy Flight based meta-heuristic. Swarm and Evolutionary Computation, 44, 1003–1017.
Wang, T.-C., & Lee, H.-D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980–8985.
Wright, S. L., Thompson, R. C., & Galloway, T. S. (2013). The physical impacts of microplastics on marine organisms: a review. Environmental Pollution, 178, 483–492.
Yan, B., Jin, J. G., Zhu, X., Lee, D.-H., Wang, L., & Wang, H. (2020). Integrated planning of train schedule template and container transshipment operation in seaport railway terminals. Transportation Research Part E: Logistics and Transportation Review, 142, 102061.
Yan, B., Zhu, X., Lee, D.-H., Jin, J. G., & Wang, L. (2020). Transshipment operations optimisation of sea-rail intermod-al container in seaport rail terminals. Computers & Industrial Engineering, 141, 106296.
Yang, Z., Ng, A. K. Y., & Wang, J. (2014). A new risk quantification approach in port facility security assessment. Transportation Research Part A: Policy and Practice, 59, 72–90.