An optimization design method for submarine cabins based on intelligent algorithms

被引:0
|
作者
Ma, Lin [1 ]
Chen, Dengkai [1 ]
Yan, Yanpu [2 ]
An, Weilan [1 ]
机构
[1] Northwestern Polytech Univ, Sch Mech Engn, Xian, Peoples R China
[2] Changan Univ, Sch Construct Machinery, Xian, Peoples R China
关键词
Submarine living cabin; Double layer cabin layout; Multi-population genetic algorithm; Multi-objective optimization; Design method; POPULATION GENETIC ALGORITHM; LAYOUT;
D O I
10.1016/j.ijnaoe.2024.100642
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
Submarine compartment layout design is a multi-objective optimization problem, which needs to consider the mutual position, passage relationship, comfort, convenience, and other aspects between compartments. Based on the characteristics of submarine living cabin layouts, this paper introduces a fuzzy evaluation method to comprehensively analyze the functional adjacency and personnel circulation relationships between compartments. Moreover, combined with emergency evacuation requirements, the study established a double layer cabin layout optimization model and proposed a multi-population genetic algorithm for optimizing the layout of submarine living cabins. Simulation experiments were conducted using MATLAB software to validate the algorithm's effectiveness. A comparison was made between the multi-population genetic algorithm and the standard genetic algorithm. The results verify the feasibility of the proposed design method and its ability to effectively address the submarine compartment layout optimization problem, thereby improving the efficiency of compartment layout optimization design.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Intelligent Design of Building Materials: Development of an AI-Based Method for Cement-Slag Concrete Design
    Zhu, Fei
    Wu, Xiangping
    Zhou, Mengmeng
    Sabri, Mohanad Muayad Sabri
    Huang, Jiandong
    MATERIALS, 2022, 15 (11)
  • [42] The Automatic Design of Multiobjective Ant Colony Optimization Algorithms
    Lopez-Ibanez, Manuel
    Stuetzle, Thomas
    IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2012, 16 (06) : 861 - 875
  • [43] Structural optimization design of machine tools based on parallel artificial neural networks and genetic algorithms
    Yiwei Ma
    Yanling Tian
    Xianping Liu
    Neural Computing and Applications, 2023, 35 : 25201 - 25221
  • [44] Intelligent design optimization of age-hardenable Al alloys
    Dey, Swati
    Sultana, Nashrin
    Dey, Partha
    Pradhan, Susanta Kumar
    Datta, Shubhabrata
    COMPUTATIONAL MATERIALS SCIENCE, 2018, 153 : 315 - 325
  • [45] Exploration of Narrative Design Method and Tool on Intelligent Cockpit Experience Design
    Xue, Zhongjie
    Zhao, Danhua
    Yang, Zijiang
    Wang, Tao
    CROSS-CULTURAL DESIGN, PT IV, CCD 2024, 2024, 14702 : 178 - 191
  • [46] Metamodel-Based Hyperparameter Optimization of Optimization Algorithms in Building Energy Optimization
    Si, Binghui
    Liu, Feng
    Li, Yanxia
    BUILDINGS, 2023, 13 (01)
  • [48] Intelligent Modeling and Optimization Method Based on Comprehensive Product Indices for Lead-Zinc Sintering Process
    Cui Kai
    Cao Weihua
    Wu Min
    Wang Chunsheng
    PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 3, 2008, : 393 - 397
  • [49] Integrated optimization design of electric power steering and suspension systems based on hierarchical coordination optimization method
    Xu, Han
    Zhao, Youqun
    Lin, Fen
    Pi, Wei
    Feng, Shilin
    STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION, 2022, 65 (02)
  • [50] Genetic algorithms development for multiobjective design optimization of compressor cascade
    Li J.
    Morinishi K.
    Satofuka N.
    Journal of Thermal Science, 1999, 8 (3) : 158 - 165