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Author Abramowski, Tomasz
Affiliation West Pomeranian University of Technology, Faculty of Maritime Technology Zachodniopomorski Uniwersytet Technologiczny, Wydział Techniki Morskiej 71-065 Szczecin, al. Piastów 41
E-mail tomasz.abramowski@zut.edu.pl
ISSN printed 1733-8670
URI https://repository.am.szczecin.pl/handle/123456789/228
Abstract The paper presents some selected results of research on applications of artificial intelligence to the optimization of main ship design parameters and hull shape coefficients with the ship transport efficiency as an objective function. Basics of ship transport formulation are concisely discussed, together with examples for different approaches to optimization. An example of neural network use for the determination of ship transport efficiency is given with an assessment of its ability for data generalization. Moreover, two optimization procedures are presented: one using genetic algorithms and the other with simulated annealing approach. Both procedures lead to the improvement of ship transport efficiency
Pages 5–11
Publisher Scientific Journals of the Maritime University of Szczecin, Zeszyty Naukowe Akademii Morskiej w Szczecinie
Keywords optimization
Keywords ship design for performance
Keywords design parameters
Title Application of artificial intelligence methods for improving ship transport efficiency
Type Original scientific article
References
  1. MAN B&W Diesel A/S: Propulsion trends for bulk car-riers. 2005.
  2. ABRAMOWSKI T., ZMUDA A.: Combining Artificial Neural Networks and Simulated Annealing Algorithm for Reduc-ing Ship Effective Power. P.J. Environmental Studies, 2008, 17, 4C, 67–71.
  3. SCHNEEKLUTH H., BERTRAM V.: Ship design for efficiency and economy. Butterworth-Heinemann, 1998. Others
  4. CHĄDZYŃSKI W.: Elementy współczesnej metodyki projek-towania obiektów pływających. Prace Naukowe Politech-niki Szczecińskiej. Szczecin 2001.
  5. ABRAMOWSKI T., ZMUDA A.: Generalization of Container Ship Design Parameters by Means of Neural Networks. P.J. Environmental Studies, 2008, 17, 4C, 111–115.
  6. Matlab User Guide, Genetic algorithm and direct search toolbox, Neural network toolbox. The MathWorks, 2008.
  7. MESBAHI E., ATLAR M.: Artificial neural networks: applica-tions in marine design and modeling. 1st Int. Conf. Com-puter Applications and Information Technology in the Maritime Industries. Potsdam 2000.
ISSN on-line 2392-0378
Language English
Funding No data
Figures 6
Tables 1
Published 2010-06-10
Accepted 2010-05-09
Recieved 2010-04-11


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