DECISION SUPPORT SYSTEM FOR THE FORMATION OF CARGO PLANS OF CONTAINER SHIPS
https://doi.org/10.33815/2313-4763.2024.1.28.175-184
Abstract
The article examines the issue of creating a decision support system (DSS) for the formation of cargo plans of container ships. The priority directions of scientific research in the field of optimization of processes of control cargo operations of container ships have been determined. It is shown that the key problem in the optimization of sea container transportation is the problem of forming optimal cargo plans. The peculiarities of the process of building a cargo placement plan on a container ship and the principles of its adjustment for the case of multiport container transportation are considered. Approaches to optimizing the process of forming a cargo plan of a container ship have been proposed. It was determined that the problem of forming the optimal cargo plan of the ship consists in solving a set of complex interrelated problems of multi-criteria optimization. With the application of a systematic approach to the analysis of the process of forming the ship's cargo plan, the key factors influencing it were determined. Based on the identified features of information processing processes in the formation of the cargo plan of a container ship, as well as the specifics of its creation and correction in the conditions of multiport transportation, the structure of the DSS was developed to manage such a process and a list of its main functions was defined. The use of flexible strategies for choosing optimization procedures that take into account the influence of the shipowner's priorities on the process of forming the ship's cargo plan is proposed. Prospective directions of further scientific research in the specified field are determined.
References
2. Twiller, J. V., Sivertsen, A., Pacino, D., Jensen, R. M. (2024). Literature survey on the container stowage planning problem. European Journal of Operational Research. vol. 317. no. 3. Р. 841–857.
3. Ambrosino, D., Sciomachen, A., Tanfani, Е. (2004). Stowing a containership: the master bay plan problem. Transportation Research Part A: Policy and Practice. № 38.2. Р. 81–99.
4. Ambrosino, D., Paolucci, M., Sciomachen, A. (2015). A MIP heuristic for multi port stowage planning. Transportation Research Procedia. P. 725–734.
5. Rahsed, D. M., Gheith, M. S., Eltawil, A. B. (2018). A Rule-based Greedy Algorithm to Solve Stowage Planning Problem. IEEE International Conference on Industrial Engineering and Engineering Management, December. P. 437–441.
6. Ben, A. P., Sokolov, A. V. (2023). Analiz suchasnoho stanu metodiv formuvannia vantazhnykh planiv konteinerovoziv ta shliakhy yikh podalshoho vdoskonalennia. Naukovyi visnyk Khersonskoi derzhavnoi morskoi akademii. №1–2 (26–27). S. 6–16.
7. Pacino, D., Delgado, A., Jensen, R., Bebbington, T. (2011). Fast generation of nearoptimal plans for eco-efficient stowage of large container vessels. Computational Logistics. P. 286–301.
8. Wang, L., Ni, M., Gao, J., Shen, Q., Jia, Y., Yao, C. (2019). The Loading Optimization: A Novel Integer Linear Programming Model. Enterprise Information Systems. Vol. 13 (10). Р. 1471–1482.
9. Tsymbal, M. M. (2020). Formuvannia planu zavantazhennia konteinerovozu. Naukovyi visnyk Khersonskoi derzhavnoi morskoi akademii. №1(22). S. 64–73.
10. Fedorov, A. I. (2019). Metod formuvannia suboptymalnoho vantazhnoho planu konteinerovozu. Problemy informatsiinykh tekhnolohii. №25. S. 96–100.
11. Lee, C.-Y., & Song, D.-P. (2017). Ocean container transport in global supply chains: Overview and research opportunities.Transportation Research Part B: Methodological. Vol. 95, P. 442–474.
12. Christensen, J., Pacino, D. (2017). A matheuristic for the cargo mix problem with block stowage. Transportation Research Part E: Logistics and Transportation Review, 97. рр. 151–171.
13. Кaмєнєв, К. I., Кaмєнєвa, А. В. (2018). Викopиcтaння адитивного aлгopитму для poзмiщення небезпечних вaнтaжiв нa кoнтейнернoму cуднi. Cудoвoждение. № 28. С. 70–77.
14. Kebedow, K. G., Oppen, J. (2018). Including containers with dangerous goods in the multi-port master bay planning problem. Mendel. vol. 24(2), P. 23–36.
15. Franzkeit, J., Schwientek, A., Jahn, C. (2020). Stowage planning for inland container vessels: A literature review. In Proceedings of the Hamburg international conference of logistics. Vol. 30. P. 247–280.
16. Parreño-Torres, C., Alvarez-Valdes, R., Parreño, F. (2019). Solution strategies for a multiport container ship stowage problem. Mathematical Problems in Engineering. vol. 2019, issue 1.
17. Yaagoubi, A. E., Alaoui, E. H., Boukachour, J. (2018). Multiobjective river-sea-going container barge stowage planning problem with container fragility and barge stability factors. GOL 2018 : The 4th International Conference on Logistics Operations Management. 1012 Apr. 2018. Le Havre, France. IEEE : Р. 214230.
18. Zhang, Z., Lee, Ch.-Y. (2016). Multiobjective approaches for the ship stowage planning problem considering ship stability and container rehandles. IEEE Transactions on Systems, Man, and Cybernetics: Systems. vol. 46(10). Р. 1374–1389.
19. Conca, A., Febbraro, A. D., Giglio, D., Rebora, F. (2018). Automation in freight port call process: Real time data sharing to improve the stowage planning. In Transportation research procedia. Vol. 30. P. 70–79.
20. Wong, E. Y. C., Ling, K. K. T., Tai, A. H., Lam, J. S. L., Zhang, X. (2022). Three-echelon slot allocation for yield and utilisation management in ship liner operations. Computers and Operations Research. 148, 105983.
21. Azevedo, A. T., Neto, L. L. S., Chaves, A. A., Moretti, A. C. (2018). Solving the 3D stowage planning problem integrated with the quay crane scheduling problem by representation by rules and genetic algorithm. Applied So Computing Journal. vol. 65. Р. 495–516.
22. Wei, L., Zhu, W., Lim, W. (2015). A goal-driven prototype column generation strategy for the multiple container loading cost minimization problem. European Journal of Operational Research. vol. 241. no. 1. Р. 39–49.
23. Zurheide, S., Fischer, K. (2015). Revenue management methods for the liner shipping industry. Flexible Services and Manufacturing Journal. 27(2). P. 200–223.
24. Delgado, A., Jensen, R. M., Guilbert, N. (2012). A placement heuristic for a commercial decision support system for container vessel stowage. In 38th Latin America conference on informatics, CLEI 2012 - conference proceedings. http://dx.doi. org/10.1109/CLEI.2012.6427181.
25. Jensen, R. M., Leknes, E., Bebbington, T. (2012). Fast interactive decision support for modifying stowage plans using binary decision diagrams. In Lecture notes in engineering and computer science: vol. 2196, P. 1555–1561.
26. Wu, Q., Xia, Q., Wu, M. (2021). Research on intelligent loading system for container ships. IOP Conference Series: Earth and Environmental Science. Earth Environ. Sci. 632 022074.
27. Jin, J., Mi, W. (2019). An AIMMS-based decision-making model for optimizing the intelligent stowage of export containers in a single bay. Discrete and Continuous Dynamical Systems - Series S. vol. 12. Number (4–5), Р. 1101–1115.
28. Nakul, Yu. A., Nikolskyi, V. V., Stovmanenko, V. S. (2017). Systema kontroliu zavantazhennia konteinerovoziv. Sudnovodinnia. №27. S. 127–136.
