Ship hull-propeller system optimization based on the multi-objective evolutionary algorithm

被引:12
|
作者
Ghassemi, Hassan [1 ]
Zakerdoost, Hassan [1 ]
机构
[1] Amirkabir Univ Technol, Dept Maritime Engn, Hafez Ave, Tehran 158754413, Iran
关键词
Multi-objective problem; hull-propeller system; lifetime fuel consumption; NSGA-II; GENETIC ALGORITHM; DESIGN;
D O I
10.1177/0954406215616655
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The optimization of the hull-propeller system of a ship has always been one of the most important aspects of design in order to reduce the costs, mechanical losses and increase the life of system components. The proposed design methodology represents a comprehensive approach to optimize the hull-propeller system simultaneously. In this study, two objective functions are considered, i. e. lifetime fuel consumption (LFC) and lifetime cost function (Cost). The mission profile of the vessel is adopted to minimize the LFC and Cost over their operational life. The well-known evolutionary algorithm based on NSGA-II is employed to handle the multi-objective problems, where the main propeller and hull coefficients are the unknown and are considered as design variables. The results are presented for a commercial container ship driven by B-series propeller. Three different engines with the same mission profile were taken and the results revealed that the proposed method is an appropriate and effective approach for finding Pareto optimal solutions distributed uniformly and is able to improve both of the objective functions significantly and other performances of the system.
引用
收藏
页码:175 / 192
页数:18
相关论文
共 50 条
  • [21] A Two-Space-Density Based Multi-objective Evolutionary Algorithm for Multi-objective Optimization
    Wang P.
    Zhang C.-S.
    Zhang B.
    Wu J.-X.
    Liu T.-T.
    [J]. 1600, Chinese Institute of Electronics (45): : 2343 - 2347
  • [22] A cluster-based evolutionary algorithm for multi-objective optimization
    Borgulya, I
    [J]. COMPUTATIONAL INTELLIGENCE: THEORY AND APPLICATIONS, PROCEEDINGS, 2001, 2206 : 357 - 368
  • [23] A Kind of Evolutionary Multi-objective Optimization Algorithm Based on AIS
    Li, Ming-song
    [J]. MATERIALS ENGINEERING AND MECHANICAL AUTOMATION, 2014, 442 : 419 - 423
  • [24] Multi-Objective Indicator Based Evolutionary Algorithm for Portfolio optimization
    Bhagavatula, Sowmya Sree
    Sanjeevi, Sriram G.
    Kumar, Divya
    Yadav, Chitranjan Kumar
    [J]. SOUVENIR OF THE 2014 IEEE INTERNATIONAL ADVANCE COMPUTING CONFERENCE (IACC), 2014, : 1206 - 1210
  • [25] An evolutionary algorithm for dynamic multi-objective optimization
    Wang, Yuping
    Dang, Chuangyin
    [J]. APPLIED MATHEMATICS AND COMPUTATION, 2008, 205 (01) : 6 - 18
  • [26] An evolutionary algorithm for constrained multi-objective optimization
    Jiménez, F
    Gómez-Skarmeta, AF
    Sánchez, G
    Deb, K
    [J]. CEC'02: PROCEEDINGS OF THE 2002 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1 AND 2, 2002, : 1133 - 1138
  • [27] An new evolutionary multi-objective optimization algorithm
    Mu, SJ
    Su, HY
    Chu, J
    Wang, YX
    [J]. CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS, 2003, : 914 - 920
  • [28] Dynamic multi-objective optimization evolutionary algorithm
    Liu, Chun-an
    Wang, Yuping
    [J]. ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 4, PROCEEDINGS, 2007, : 456 - +
  • [29] Dynamical multi-objective optimization evolutionary algorithm
    Xiong, SW
    Li, F
    Wang, W
    Feng, C
    [J]. THIRD INTERNATIONAL SYMPOSIUM ON MULTISPECTRAL IMAGE PROCESSING AND PATTERN RECOGNITION, PTS 1 AND 2, 2003, 5286 : 418 - 421
  • [30] Hydrodynamic optimization of ship's hull-propeller system under multiple operating conditions using MOEA/D
    Zakerdoost, Hassan
    Ghassemi, Hassan
    [J]. JOURNAL OF MARINE SCIENCE AND TECHNOLOGY, 2021, 26 (02) : 419 - 431