Multi-Objective Optimization of Marine Winch Based on Surrogate Model and MOGA

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Publicado en:Computer Modeling in Engineering & Sciences vol. 143, no. 2 (2025), p. 1689
Autor principal: Jin, Chunhuan
Otros Autores: Zhu, Linsen, Liu, Quanliang, Lin, Ji
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Tech Science Press
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022 |a 1526-1492 
022 |a 1526-1506 
024 7 |a 10.32604/cmes.2025.063850  |2 doi 
035 |a 3218152445 
045 2 |b d20250101  |b d20251231 
100 1 |a Jin, Chunhuan 
245 1 |a Multi-Objective Optimization of Marine Winch Based on Surrogate Model and MOGA 
260 |b Tech Science Press  |c 2025 
513 |a Journal Article 
520 3 |a This study proposes a multi-objective optimization framework for electric winches in fiber-reinforced plastic (FRP) fishing vessels to address critical limitations of conventional designs, including excessive weight, material inefficiency, and performance redundancy. By integrating surrogate modeling techniques with a multi-objective genetic algorithm (MOGA), we have developed a systematic approach that encompasses parametric modeling, finite element analysis under extreme operational conditions, and multi-fidelity performance evaluation. Through a 10-t electric winch case study, the methodology’s effectiveness is demonstrated via parametric characterization of structural integrity, stiffness behavior, and mass distribution. The comparative analysis identified optimal surrogate models for predicting key performance metrics, which enabled the construction of a robust multi-objective optimization model. The MOGA-derived Pareto solutions produced a design configuration achieving 7.86% mass reduction, 2.01% safety factor improvement, and 23.97% deformation mitigation. Verification analysis confirmed the optimization scheme’s reliability in balancing conflicting design requirements. This research establishes a generalized framework for marine deck machinery modernization, particularly addressing the structural compatibility challenges in FRP vessel retrofitting. The proposed methodology demonstrates significant potential for facilitating sustainable upgrades of fishing vessel equipment through systematic performance optimization. 
653 |a Modernization 
653 |a Finite element method 
653 |a Performance measurement 
653 |a Configuration management 
653 |a Performance evaluation 
653 |a Safety factors 
653 |a Genetic algorithms 
653 |a Fiber reinforced plastics 
653 |a Structural integrity 
653 |a Optimization 
653 |a Mass distribution 
653 |a Pareto optimization 
653 |a Ship decks 
653 |a Winches 
653 |a Deformation analysis 
653 |a Retrofitting 
653 |a Multiple objective analysis 
653 |a Structural analysis 
653 |a Vessels 
653 |a Fishing 
653 |a Optimization models 
653 |a Redundancy 
700 1 |a Zhu, Linsen 
700 1 |a Liu, Quanliang 
700 1 |a Lin, Ji 
773 0 |t Computer Modeling in Engineering & Sciences  |g vol. 143, no. 2 (2025), p. 1689 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3218152445/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3218152445/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch