Ship design optimization in the multimodal logistics framework

E.K. Boulougouris, C. Gohari, A.D. Papanikolaou

Research output: Contribution to journal › Article

1 Citation (Scopus)

Abstract

The significance of multimodal transportation systems has worldwide increased significantly over the past two decades. European Union, United States and Japan have increased their efforts in studying the dynamics of multimodal transportation networks. In the paper about recent research work on the optimization problem of the design of ferries and Ro-Ro cargo ships using pattern recognition techniques (Artificial Neural Networks), Multi-objective Genetic Algorithms (MOGA) and the know-how created through the EU FP6 Research Project LOGBASED. A case study on the transportation of agricultural goods from the Greek Island of Crete to the markets of Munich is presented. The results of this study prove useful for the assessment of viable solutions serving in a balanced way for the interests of shipyards, ship operators, cargo owners, banking and financial institutions, investors and government administrations in the framework of optimized transportation scenarios.
LanguageEnglish
Pages150-159
Number of pages10
JournalJournal of Harbin Engineering University
Volume27
Issue numberSupp 2
Publication statusPublished - 31 Dec 2006

Fingerprint

Multimodal transportation
Logistics
Ships
Shipyards
Pattern recognition
Genetic algorithms
Neural networks
Design optimization

Keywords

  • logistics based ship design
  • genetic algorithms
  • multi-modal transportation
  • multi-objective-optimization
  • neural networks
  • computer aided design
  • optimisation
  • pattern recognition
  • structural design
  • ships

Cite this

Boulougouris, E.K. ; Gohari, C. ; Papanikolaou, A.D. / Ship design optimization in the multimodal logistics framework. In: Journal of Harbin Engineering University . 2006 ; Vol. 27, No. Supp 2. pp. 150-159.
@article{b8c0c956948e4e4a8c96f02db4750489,
title = "Ship design optimization in the multimodal logistics framework",
abstract = "The significance of multimodal transportation systems has worldwide increased significantly over the past two decades. European Union, United States and Japan have increased their efforts in studying the dynamics of multimodal transportation networks. In the paper about recent research work on the optimization problem of the design of ferries and Ro-Ro cargo ships using pattern recognition techniques (Artificial Neural Networks), Multi-objective Genetic Algorithms (MOGA) and the know-how created through the EU FP6 Research Project LOGBASED. A case study on the transportation of agricultural goods from the Greek Island of Crete to the markets of Munich is presented. The results of this study prove useful for the assessment of viable solutions serving in a balanced way for the interests of shipyards, ship operators, cargo owners, banking and financial institutions, investors and government administrations in the framework of optimized transportation scenarios.",
keywords = "logistics based ship design, genetic algorithms , multi-modal transportation, multi-objective-optimization, neural networks, computer aided design, optimisation, pattern recognition, structural design, ships",
author = "E.K. Boulougouris and C. Gohari and A.D. Papanikolaou",
year = "2006",
month = "12",
day = "31",
language = "English",
volume = "27",
pages = "150--159",
journal = "Journal of Harbin Engineering University",
issn = "1006-7043",
publisher = "Harbin Engineering University",
number = "Supp 2",

}

Boulougouris, EK, Gohari, C & Papanikolaou, AD 2006, 'Ship design optimization in the multimodal logistics framework' Journal of Harbin Engineering University , vol. 27, no. Supp 2, pp. 150-159.

Ship design optimization in the multimodal logistics framework. / Boulougouris, E.K.; Gohari, C.; Papanikolaou, A.D.

In: Journal of Harbin Engineering University , Vol. 27, No. Supp 2, 31.12.2006, p. 150-159.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Ship design optimization in the multimodal logistics framework

AU - Boulougouris, E.K.

AU - Gohari, C.

AU - Papanikolaou, A.D.

PY - 2006/12/31

Y1 - 2006/12/31

N2 - The significance of multimodal transportation systems has worldwide increased significantly over the past two decades. European Union, United States and Japan have increased their efforts in studying the dynamics of multimodal transportation networks. In the paper about recent research work on the optimization problem of the design of ferries and Ro-Ro cargo ships using pattern recognition techniques (Artificial Neural Networks), Multi-objective Genetic Algorithms (MOGA) and the know-how created through the EU FP6 Research Project LOGBASED. A case study on the transportation of agricultural goods from the Greek Island of Crete to the markets of Munich is presented. The results of this study prove useful for the assessment of viable solutions serving in a balanced way for the interests of shipyards, ship operators, cargo owners, banking and financial institutions, investors and government administrations in the framework of optimized transportation scenarios.

AB - The significance of multimodal transportation systems has worldwide increased significantly over the past two decades. European Union, United States and Japan have increased their efforts in studying the dynamics of multimodal transportation networks. In the paper about recent research work on the optimization problem of the design of ferries and Ro-Ro cargo ships using pattern recognition techniques (Artificial Neural Networks), Multi-objective Genetic Algorithms (MOGA) and the know-how created through the EU FP6 Research Project LOGBASED. A case study on the transportation of agricultural goods from the Greek Island of Crete to the markets of Munich is presented. The results of this study prove useful for the assessment of viable solutions serving in a balanced way for the interests of shipyards, ship operators, cargo owners, banking and financial institutions, investors and government administrations in the framework of optimized transportation scenarios.

KW - logistics based ship design

KW - genetic algorithms

KW - multi-modal transportation

KW - multi-objective-optimization

KW - neural networks

KW - computer aided design

KW - optimisation

KW - pattern recognition

KW - structural design

KW - ships

UR - http://heuxb.hrbeu.edu.cn/

M3 - Article

VL - 27

SP - 150

EP - 159

JO - Journal of Harbin Engineering University

T2 - Journal of Harbin Engineering University

JF - Journal of Harbin Engineering University

SN - 1006-7043

IS - Supp 2

ER -

Boulougouris EK, Gohari C, Papanikolaou AD. Ship design optimization in the multimodal logistics framework. Journal of Harbin Engineering University . 2006 Dec 31;27(Supp 2):150-159.

Access to Document