Modelling and implementation of an intelligent stowage simulator for container ships

被引:0
作者
Wang Q. [1 ]
Zhao J. [1 ]
Ma L. [1 ]
机构
[1] Navigation College, Dalian Maritime University
基金
中国国家自然科学基金;
关键词
BLOCK algorithm; Container ship; Floating condition; Intelligent stowage simulator; Restowage; Segregations; Stability; Strength;
D O I
10.1504/IJSPM.2020.107324
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
To solve the problems that conventional loading master for container ship merely provides the stability, strength, floating condition, etc. a comprehensive intelligent simulator was worked out, which can also obtain the amount of restowage containers, verify segregation scheme for dangerous containers, etc. BLOCK algorithm is proposed for the first time for restowage problems with respect to the containers on deck jam that in hold and all in hold or on deck. In the case of all in hold or on deck, independent stowage and mix stowage are studied in some detail. A fast and effective algorithm is also put forward to perform the segregation verifying. At last, the above proposed algorithms are verified by the loading condition from the loading manual. © 2020 Inderscience Enterprises Ltd.
引用
收藏
页码:201 / 212
页数:11
相关论文
共 21 条
[1]  
Ambrosino D., Anghinolfi D., Paolucci M., Sciomachen A., An experimental comparison of different heuristics for the master bay plan problem, Experimental Algorithms, pp. 314-325, (2010)
[2]  
Azevedo G.R.D., Balino J.L., Burr K.P., Linear stability analysis for severe slugging: Sensitivity to void fraction and friction pressure drop correlations, International Journal of Simulation and Process Modelling, 12, 3-4, pp. 235-248, (2017)
[3]  
Berend D., Cohen S., Shimony S.E., Zucker S., Optimal ordering of tests with extreme dependencies, Modelling, Computation and Optimization in Information Systems and Management Sciences, pp. 81-92, (2015)
[4]  
Cruz-Reyes L., Hernandez P., Melin H.P., Fraire H.J., Mar J.O., Constructive algorithm for a benchmark in ship stowage planning, Recent Advances on Hybrid Intelligent Systems (Studies in Computational Intelligence), 451, pp. 393-408, (2013)
[5]  
Deb K., Jain H., An evolutionary many-objective optimization algorithm using reference-point-based non-dominated sorting approach, part I: Solving problems with box constraints, IEEE Trans. Evol. Comput., 18, 4, pp. 577-601, (2014)
[6]  
Delgado A., Jensen R.M., Janstrup K., Rose T.H., Andersen K.H., A constraint programming model for fast optimal stowage of container vessel bays, European Journal of Operational Research, 220, 1, pp. 251-261, (2012)
[7]  
Ding D., Chou M.C., Stowage planning for container ships: A heuristic algorithm to reduce the number of shifts, European Journal of Operational Research, 246, pp. 242-249, (2015)
[8]  
Dubrovsky O., Levitin G., Penn M., A genetic algorithm with a compact solution encoding for the container ship stowage problem, Journal of Heuristics, 8, 6, pp. 585-599, (2002)
[9]  
Galrao R.A., Jacob J., Justo J.F., Cargo dynamic stability in the container loading problem - A physics simulation tool approach, International Journal of Simulation and Process Modelling, 13, 1, pp. 15-23, (2017)
[10]  
Hu M., Cai W., Multi-objective optimization based on improved genetic algorithm for containership stowage, International Conference on Industrial Engineering and Applications, pp. 224-228, (2017)