收藏切换
Improved Hybrid PSO-Based Dynamic Cable Optimization Design
收藏切换
PDF
Le SUN1, Qingfeng DUAN2, *, Chen AN3, Menglan DUAN4
Ship Engineering | 2026, 48(3) : 170 - 180
Less
收藏切换
Ship Engineering | 2026, 48(3): 170-180
Ocean Engineering
Improved Hybrid PSO-Based Dynamic Cable Optimization Design
Full
Le SUN1, Qingfeng DUAN2, *, Chen AN3, Menglan DUAN4
Affiliations
  • 1.PipeChina Network Corporation Eastern Oil Storage and Transportation Co., Ltd., Xuzhou 221008, Jiangsu, China
  • 2.CNOOC Research Institute, Beijing 100028, China
  • 3.College of Safety and Ocean Engineering, China University of Petroleum-Beijing, Beijing 102249, China
  • 4.Tsinghua Shenzhen International Graduate School, Tsinghua University, Beijing 100084, China
Published: 2026-03-25 doi: 10.13788/j.cnki.cbgc.2026.03.19
Outline
收藏切换
[Purpose]

To effectively reduce fatigue damage, a reasonable dynamic cable design is required.

[Method]

An optimization model based on an improved hybrid particle swarm optimization algorithm is established. It employ MATLAB to develop a genetic-chaotic particle swarm dynamic factor optimization algorithm and utilize the Orcaflex software for the overall design and optimization of platform dynamic cables. The optimization problem of deepwater dynamic cables is treated as the objective function, with parameters such as cable length, buoyancy block and counterweight block positions, and spacing as optimization variables. Building upon the foundation of the standard particle swarm algorithm and integrating genetic algorithms, it effectively prevent dynamic cable optimization parameters from falling into local optima. Chaotic initialization of initial particles is applied to ensure a uniform distribution in high-dimensional solution spaces. Dynamic inertia weight factors and learning factors are introduced to balance global and local search capabilities during optimization. Adhering to the Pareto principle, It formulate an objective function to facilitate multi-objective constrained optimization. The improved optimization algorithm shows better performance in terms of convergence, accuracy, and convergence speed.

[Result]

It quickly and effectively balances the relationship between the maximum axial tension and the minimum bending radius of the cable and pipe, achieves the optimal design.

[Conclusion]

It provides strong support and guidance for practical engineering applications.

hybrid particle swarm optimization (PSO)  /  genetic algorithm (GA)  /  chaotic initialization  /  dynamic factors  /  multi-objective constraints  /  MATLAB  /  Orcaflex
Le SUN, Qingfeng DUAN, Chen AN, Menglan DUAN. Improved Hybrid PSO-Based Dynamic Cable Optimization Design[J]. Ship Engineering, 2026 , 48 (3) : 170 -180 . DOI: 10.13788/j.cnki.cbgc.2026.03.19
Year 2026 volume 48 Issue 3
PDF
44
7
Cite this Article
BibTeX
Article Info
doi: 10.13788/j.cnki.cbgc.2026.03.19
  • Receive Date:2025-05-10
  • Online Date:2026-04-24
  • Published:2026-03-25
Article Data
Affiliations
History
  • Received:2025-05-10
  • Revised:2025-09-22
Affiliations
    1.PipeChina Network Corporation Eastern Oil Storage and Transportation Co., Ltd., Xuzhou 221008, Jiangsu, China
    2.CNOOC Research Institute, Beijing 100028, China
    3.College of Safety and Ocean Engineering, China University of Petroleum-Beijing, Beijing 102249, China
    4.Tsinghua Shenzhen International Graduate School, Tsinghua University, Beijing 100084, China
References
Share
https://castjournals.cast.org.cn/joweb/cbgc/EN/10.13788/j.cnki.cbgc.2026.03.19
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT