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Branch pipe routing based on 3D connection graph and concurrent ant colony optimization algorithm

Author

Listed:
  • Yanfeng Qu

    (Shanghai Jiao Tong University)

  • Dan Jiang

    (Shanghai Jiao Tong University)

  • Qingyan Yang

    (Shanghai Jiao Tong University)

Abstract

Pipe routing, in particular branch pipes with multiple terminals, has an important influence on product performance and reliability. This paper develops a new rectilinear branch pipe routing approach for automatic generation of the optimal rectilinear branch pipe routes in constrained spaces. Firstly, this paper presents a new 3D connection graph, which is constructed by extending a new 2D connection graph. The new 2D connection graph is constructed according to five criteria in discrete Manhattan spaces. The 3D connection graph can model the 3D constrained layout space efficiently. The length of pipelines and the number of bends are modeled as the optimal design goal considering the number of branch points and three types of engineering constraints. Three types of engineering constraints are modeled by this 3D graph and potential value. Secondly, a new concurrent Max–Min Ant System optimization algorithm, which adopts concurrent search strategy and dynamic update mechanism, is used to solve Rectilinear Branch Pipe Routing optimization problem. This algorithm can improve the search efficiency in 3D constrained layout space. Numerical comparisons with other current approaches in literatures demonstrate the efficiency and effectiveness of the proposed approach. Finally, a case study of pipe routing for aero-engines is conducted to validate this approach.

Suggested Citation

  • Yanfeng Qu & Dan Jiang & Qingyan Yang, 2018. "Branch pipe routing based on 3D connection graph and concurrent ant colony optimization algorithm," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1647-1657, October.
    • Handle: RePEc:spr:joinma:v:29:y:2018:i:7:d:10.1007_s10845-016-1203-4
    DOI: 10.1007/s10845-016-1203-4
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    Citations

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    Cited by:

    1. Saekyeol Kim & Taehyeok Choi & Shinyu Kim & Taejoon Kwon & Tae Hee Lee & Kwangrae Lee, 2021. "Sequential graph-based routing algorithm for electrical harnesses, tubes, and hoses in a commercial vehicle," Journal of Intelligent Manufacturing, Springer, vol. 32(4), pages 917-933, April.
    2. Xinjian Deng & Jianhua Liu & Hao Gong & Jiayu Huang, 2023. "A novel vision-based method for loosening detection of marked T-junction pipe fittings integrating GAN-based segmentation and SVM-based classification algorithms," Journal of Intelligent Manufacturing, Springer, vol. 34(6), pages 2581-2597, August.
    3. Qiaoyu Zhang & Yan Lin, 2024. "Integrating multi-agent reinforcement learning and 3D A* search for facility layout problem considering connector-assembly," Journal of Intelligent Manufacturing, Springer, vol. 35(7), pages 3393-3418, October.

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