Optimal Design of Ship Branch Pipe Route by a Cooperative Co-Evolutionary Improved Particle Swarm Genetic Algorithm

This paper proposes a cooperative co-evolutionary improved particle swarm genetic (CCIPSG) algorithm for ship branch pipe route design (SBPRD) based on the strategy of first decomposition and then reconstruction. SBPRD is a common type of ship pipe route design connecting one start point and several end points with various performance constraints in 3-D space. The traditional optimization method of SBPRD needs to select the laying sequence of branch pipelines, determine the branch points, and finally conduct the pipeline layout, which is full of uncertainty. The CCIPSG algorithm proposed in this paper aims to avoid the uncertainty of laying sequence and branch points by using the strategy of decomposition before reconstruction. The branch pipe route is deemed as a system; through the process of decomposing, the branch pipe route is decomposed as several single pipe routes with a common start point and different end points. After obtaining the optimal solutions of each single pipe route by using the improved particle swarm genetic algorithm, the co-evolutionary mechanism and overlapped potential energy value method are used to reconstruct the branch pipeline with the minimum total path length and elbows. Compared with the conventional method, the CCIPSG algorithm could not only automatically determinate the laying sequence and branch points but also improve the convergence speed and the quality of the solution. Finally, the simulation result demonstrates the feasibility and efficiency of the proposed method.

• Record URL:
  http://dx.doi.org/10.4031/MTSJ.55.5.18
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/1623789
• Supplemental Notes:
  • Copyright © 2021 Marine Technology Society, Inc.
• Authors:
  • Wang, Yunlong
  • Wei, Hao
  • Zhang, Xin
  • Li, Kai
  • Guan, Guan
  • Jin, Chaoguan
  • Yan, Lin
• Publication Date: 2021-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 116-128
• Serial:
  • Marine Technology Society Journal
  • Volume: 55
  • Issue Number: 5
  • Publisher: Marine Technology Society
  • ISSN: 0025-3324
  • Serial URL: http://ingentaconnect.com/content/mts/mtsj

Subject/Index Terms

• TRT Terms: Genetic algorithms; Optimization; Pipe; Ships; Vehicle design
• Subject Areas: Design; Marine Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01789277
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 23 2021 8:59AM