Abstract
This paper describes a randomized algorithm with Tabu Search (TS) for multi-objective optimization of large containership stowage plans. The algorithm applies a randomized block-based container allocation approach to obtain a Pareto set of stowage plans from a set of initial solutions in the first stage, and uses TS to carry out multi-objective optimization on the Pareto set of stowage plans in the second stage. Finally, a group of non-dominated solutions is generated based on objectives such as the number of re-handles, the completion time of the longest crane, the number of stacks that exceed the weight limit, the number of idle slots, horizontal moment difference and cross moment difference. Experimental results based on real data show that the proposed algorithm is able to obtain better stowage plans compared with human planners.
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References
Ambrosino, D., Sciomachen, A., Tanfani, E.: Stowing a Containership: the Master Bay Plan Problem. Transportation Research 38, 81–99 (2004)
Avriel, M., Penn, M., Shpirer, N., Witteboon, S.: Stowage planning for container ships to reduce the number of shifts. Annals of Operation Research 76, 55–71 (1998)
Avriel, M., Penn, M., Shpirer, N.: Containership stowage problem: complexity and connection capabilities. Discrete Applied Mathematics 103, 271–279 (2000)
Ebeling, C.E.: Evolution of a Box. American Heritage of Invention and Technology 23(4), 8–9 (2009)
Glover, F.: Heuristics for Integer Programming Using Surrogate Constraints. Decision Science 8, 156–166 (1977)
Glover, F., Taillard, E., de Werra, D.: A User Guide to Tabu Search. Annals of Operations Research 41, 3–28 (1993)
Kang, J.-G., Kim, Y.-D.: Stowage Planning in Maritime Container Transportation. Journal of the Operational Research Society 53, 415–426 (2002)
Liu, F., Low, M.Y.H., Huang, S.Y., Hsu, W.J., Zeng, M., Win, C.A.: Stowage Planning of Large Containership with tradeoff between Crane Workload Balance and Ship Stability. In: Proceedings of the 2010 IAENG International Conference on Industrial Engineering, pp. 1537–1543 (2010)
http://www.maerskline.com/link/?page=brochure&path=/our_services/vessels , accessed on (April 25, 2011)
Wilson, I.D., Roach, P.A.: Principles of combinatorial optimization applied to container-ship stowage planning. Journal of Heuristics 5, 403–418 (1999)
Wilson, I.D., Roach, P.A.: Container stowage planning: a methodology for generating computerized solutions. Journal of Operational Research Society 51, 1248–1255 (2000)
Xiao, X., Low, M.Y.H., Liu, F., Huang, S.Y., Hsu, W.J., Li, Z.: An Efficient Block-Based Heuristic Method for Stowage Planning of Large Containerships with Crane Split Consideration. In: Proceedings of the International Conference on Harbour, Maritime & Multimodal Logistics Modelling and Simulation, pp. 93–99 (2009)
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Liu, F., Low, M.Y.H., Hsu, W.J., Huang, S.Y., Zeng, M., Win, C.A. (2011). Randomized Algorithm with Tabu Search for Multi-Objective Optimization of Large Containership Stowage Plans. In: Böse, J.W., Hu, H., Jahn, C., Shi, X., Stahlbock, R., Voß, S. (eds) Computational Logistics. ICCL 2011. Lecture Notes in Computer Science, vol 6971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24264-9_20
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DOI: https://doi.org/10.1007/978-3-642-24264-9_20
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