Multi-Objective Optimization Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization for Pipeline Selection of Replenishment Oiler
Ship pipeline selection, as a crucial component of ship pipeline design, is often a time-consuming process due to its high complexity. In this study, the response surface methodology combined with the multi-objective particle swarm optimization algorithm was used to optimize the fuel pipeline resist...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/13/6/1037 |
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| author | Yujin Cong Cheng Meng Ming Yang Yong Liu Ping Yi Tie Li Shuai Huang |
| author_facet | Yujin Cong Cheng Meng Ming Yang Yong Liu Ping Yi Tie Li Shuai Huang |
| author_sort | Yujin Cong |
| collection | DOAJ |
| description | Ship pipeline selection, as a crucial component of ship pipeline design, is often a time-consuming process due to its high complexity. In this study, the response surface methodology combined with the multi-objective particle swarm optimization algorithm was used to optimize the fuel pipeline resistance and its space volume, aiming to select the optimal design scheme for an X-type replenishment oiler. Firstly, a one-dimensional pipeline system simulation model of a replenishment oiler was established based on the Flowmaster software (version 4.2_0 2020), and the fueling process was simulated. The simulation results were validated against the experimental results, and good agreements were obtained. Then, the response surface methodology was employed to establish regression models for the pipeline resistance, pipeline space volume, and imbalance degree of branch flows. Finally, multi-objective particle swarm optimization was used to optimize the target and select the optimal virtual solution from the Pareto front. Constrained by the international application standard, the optimal real solution was determined. Compared with the original scheme, the optimized scheme reduced the resistance by 3.57% for the #1 pipeline system and by 3.51% for the #2 pipeline system, respectively, and the space volume of the pipeline system was reduced by 5.72% while ensuring the flow balance. |
| format | Article |
| id | doaj-art-ba7f28a1a20340468ab31e514509940a |
| institution | Kabale University |
| issn | 2077-1312 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj-art-ba7f28a1a20340468ab31e514509940a2025-08-20T03:27:19ZengMDPI AGJournal of Marine Science and Engineering2077-13122025-05-01136103710.3390/jmse13061037Multi-Objective Optimization Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization for Pipeline Selection of Replenishment OilerYujin Cong0Cheng Meng1Ming Yang2Yong Liu3Ping Yi4Tie Li5Shuai Huang6State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaMarine Design & Research Institute of China, Shanghai 200011, ChinaMarine Design & Research Institute of China, Shanghai 200011, ChinaMarine Design & Research Institute of China, Shanghai 200011, ChinaState Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaState Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaState Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University, Shanghai 200240, ChinaShip pipeline selection, as a crucial component of ship pipeline design, is often a time-consuming process due to its high complexity. In this study, the response surface methodology combined with the multi-objective particle swarm optimization algorithm was used to optimize the fuel pipeline resistance and its space volume, aiming to select the optimal design scheme for an X-type replenishment oiler. Firstly, a one-dimensional pipeline system simulation model of a replenishment oiler was established based on the Flowmaster software (version 4.2_0 2020), and the fueling process was simulated. The simulation results were validated against the experimental results, and good agreements were obtained. Then, the response surface methodology was employed to establish regression models for the pipeline resistance, pipeline space volume, and imbalance degree of branch flows. Finally, multi-objective particle swarm optimization was used to optimize the target and select the optimal virtual solution from the Pareto front. Constrained by the international application standard, the optimal real solution was determined. Compared with the original scheme, the optimized scheme reduced the resistance by 3.57% for the #1 pipeline system and by 3.51% for the #2 pipeline system, respectively, and the space volume of the pipeline system was reduced by 5.72% while ensuring the flow balance.https://www.mdpi.com/2077-1312/13/6/1037pipeline systemreplenishment oilerFlowmaster simulationresponse surface methodologymulti-objective particle swarm optimization |
| spellingShingle | Yujin Cong Cheng Meng Ming Yang Yong Liu Ping Yi Tie Li Shuai Huang Multi-Objective Optimization Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization for Pipeline Selection of Replenishment Oiler Journal of Marine Science and Engineering pipeline system replenishment oiler Flowmaster simulation response surface methodology multi-objective particle swarm optimization |
| title | Multi-Objective Optimization Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization for Pipeline Selection of Replenishment Oiler |
| title_full | Multi-Objective Optimization Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization for Pipeline Selection of Replenishment Oiler |
| title_fullStr | Multi-Objective Optimization Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization for Pipeline Selection of Replenishment Oiler |
| title_full_unstemmed | Multi-Objective Optimization Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization for Pipeline Selection of Replenishment Oiler |
| title_short | Multi-Objective Optimization Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization for Pipeline Selection of Replenishment Oiler |
| title_sort | multi objective optimization based on response surface methodology and multi objective particle swarm optimization for pipeline selection of replenishment oiler |
| topic | pipeline system replenishment oiler Flowmaster simulation response surface methodology multi-objective particle swarm optimization |
| url | https://www.mdpi.com/2077-1312/13/6/1037 |
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