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A heuristic approach to optimizing the loading of homogeneous marine cargo

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Języki publikacji
EN
Abstrakty
EN
In this article, the optimal loading of homogeneous marine cargo is considered. A mathematical formulation in terms of a mixed-integer linear program can be given. Still, the level of complexity turns out to be too high to perform full-scale computations. On the one hand, the reasons for this are the multitude of variables and constraints. On the other hand, feasible solutions to such problems may often be economically unacceptable or simply empty. Therefore, a heuristic is presented, according to which the relaxation of the limiting conditions influencing the solution’s feasibility and its economic profitability was parametrized. Under this heuristic, shifting the deadlines of selected orders is allowed. Also, the assignment of orders to vessels is separated from the allocation of vessels to piers in loading and unloading ports. The solution presented can be easily generalized by adding additional restrictions or features like indirect vessels, founding cost, or differentiation between materials.
Rocznik
Strony
1--15
Opis fizyczny
Bibliogr. 25 poz., tab.
Twórcy
  • Institute of Econometrics, Collegium of Economic Analysis, SGH Warsaw School of Economics, Poland
Bibliografia
  • [1] Andersen, K., Andersson, H., Christiansen, M., Grønhaug, R., and Sjamsutdinov, A. Designing a maritime supply chain for distribution of wood pellets: a case study from southern Norway. Flexible Services and Manufacturing Journal 29, 3 (2017), 572–600.
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  • [3] Bortfeldt, A., and Gehring, H. Applying tabu search to container loading problems. In Operations Research Proceedings 1997 (Berlin, Heidelberg, 1998), Springer Berlin Heidelberg, pp. 533–538.
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  • [5] Castillo-Villar, K. K., González-Ramírez, R. G., González, P. M., and Smith, N. R. A heuristic procedurę for a ship routing and scheduling problem with variable speed and discretized time windows. Mathematical Problems in Engineering (2014), 1–14.
  • [6] Chang, Y.-T., Tongzon, J., Luo, M., and Lee, P. T.-W. Estimation of optimal handling capacity of a container port: An economic approach. Transport Reviews 32, 2 (2012), 241–258.
  • [7] Christiansen, M., and Fagerholt, K. Maritime inventory routing problems. In Encyclopedia of Optimization, C. Floudas and P. M. Pardalos, Eds., 2 ed. Springer US, Boston, MA, 2009, pp. 1947–1955.
  • [8] Christiansen, M., Fagerholt, K., Hasle, G., Minsaas, A., and Nygreen, B. Maritime transport optimization: An ocean of opportunities. ORMS Today 36, 2 (2009), 26–31.
  • [9] Golias, M. M., Boile, M., Theofanis, S., and Efstathiou, C. The berth-scheduling problem: Maximizing berth productivity and minimizing fuel consumption and emissions production. Transportation Research Record: Journal of the Transportation Research Board 2166, 1 (2010), 20–27.
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  • [12] Guze, S., Neumann, T., and Wilczyński, P. Multi-criteria optimisation of liquid cargo transport according to linguistic approach to the route selection task. Polish Maritime Research 24, s1 (2017), 89–96.
  • [13] Hess, M., and Hess, S. Optimization of ship cargo operations by genetic algorithm. Promet - Traffic&Transportation 21, 4 (2009), 239–245.
  • [14] Hess, M., and Hess, S. Multi-objective ship’s cargo handling model. Transport 30, 1 (2015), 55–60.
  • [15] Lee, P. T.-W., and Yang, Z. Multi-Criteria Decision Making in Maritime Studies and Logistics. Applications and Cases. Springer, 2018.
  • [16] Lisowski, J. Optimization methods in maritime transport and logistics. Polish Maritime Research 25, 4 (2018), 30–38.
  • [17] Nikolaou, M. Optimizing the logistics of compressed natural gas transportation by marine vessels. Journal of Natural Gas Science and Engineering 2, 1 (2010), 1–20.
  • [18] Persson, J. A., and Göthe-Lundgren, M. Shipment planning at oil refineries using column generation and valid inequalities. European Journal of Operational Research 163, 3 (2005), 631–652.
  • [19] Simongáti, G. Multi-criteria decision making support tool for freight integrators: Selecting the most sustainable alternative. Transport 25, 1 (2010), 89–97.
  • [20] Song, D.-P., Li, D., and Drake, P. Multi-objective optimization for planning liner shipping service with uncertain port times. Transportation Research Part E: Logistics and Transportation Review 84 (2015), 1–22.
  • [21] Umang, N., Bierlaire, M., and Vacca, I. Exact and heuristic methods to solve the berth allocation problem in bulk ports. Transportation Research Part E: Logistics and Transportation Review 54 (2013), 14–31.
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  • [23] Xiang, X., Yu, C., Xu, H., and Zhu, S. X. Optimization of heterogeneous container loading problem with adaptive genetic algorithm. Complexity (2018), 1–12.
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Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-decb5b47-3569-4a60-a78d-38deb33b4382
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