Research on Recommendation Method of Product Design Scheme Based on Multi-Way Tree and Learning-to-Rank
A product is composed of several components, and the number, type, and combination of components plays a crucial role in the process of product design. It is difficult to get an optimized scheme in a short time. In order to improve the efficiency of product design, a product design scheme recommenda...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Machines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-1702/8/2/30 |
| _version_ | 1797565996051988480 |
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| author | Boyang Chen Xiaobing Hu Yunliang Huo Xi Deng |
| author_facet | Boyang Chen Xiaobing Hu Yunliang Huo Xi Deng |
| author_sort | Boyang Chen |
| collection | DOAJ |
| description | A product is composed of several components, and the number, type, and combination of components plays a crucial role in the process of product design. It is difficult to get an optimized scheme in a short time. In order to improve the efficiency of product design, a product design scheme recommendation algorithm based on multi-way tree and learning-to-rank is proposed. Firstly, the product solution model, whose nodes are obtained by mapping the product attributes, is generated according to the design process, and the alternative scheme is obtained by traversing the multi-tree model. Secondly, considering users’ cognition of the importance of each product attribute, the analytic hierarchy process (AHP) is applied to assign weight to the product attribute, and then similarity to ideal solution (TOPSIS) method based on AHP is used to rank alternative solutions. Furthermore, according to users’ preference for parts’ supplier information, the learning-to-rank algorithm is used to optimize the list of alternative schemes twice. Finally, taking the design of the hoist as an example, it was verified that the proposed method had higher efficiency and better recommendation effect than the traditional parametric design method. |
| first_indexed | 2024-03-10T19:20:34Z |
| format | Article |
| id | doaj.art-2762124ffaf7477eb301807448f630f2 |
| institution | Directory Open Access Journal |
| issn | 2075-1702 |
| language | English |
| last_indexed | 2024-03-10T19:20:34Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj.art-2762124ffaf7477eb301807448f630f22023-11-20T02:59:41ZengMDPI AGMachines2075-17022020-06-01823010.3390/machines8020030Research on Recommendation Method of Product Design Scheme Based on Multi-Way Tree and Learning-to-RankBoyang Chen0Xiaobing Hu1Yunliang Huo2Xi Deng3School of Mechanical Engineering, Sichuan University, Chengdu 610065, ChinaSchool of Mechanical Engineering, Sichuan University, Chengdu 610065, ChinaSchool of Mechanical Engineering, Sichuan University, Chengdu 610065, ChinaSchool of Mechanical Engineering, Sichuan University, Chengdu 610065, ChinaA product is composed of several components, and the number, type, and combination of components plays a crucial role in the process of product design. It is difficult to get an optimized scheme in a short time. In order to improve the efficiency of product design, a product design scheme recommendation algorithm based on multi-way tree and learning-to-rank is proposed. Firstly, the product solution model, whose nodes are obtained by mapping the product attributes, is generated according to the design process, and the alternative scheme is obtained by traversing the multi-tree model. Secondly, considering users’ cognition of the importance of each product attribute, the analytic hierarchy process (AHP) is applied to assign weight to the product attribute, and then similarity to ideal solution (TOPSIS) method based on AHP is used to rank alternative solutions. Furthermore, according to users’ preference for parts’ supplier information, the learning-to-rank algorithm is used to optimize the list of alternative schemes twice. Finally, taking the design of the hoist as an example, it was verified that the proposed method had higher efficiency and better recommendation effect than the traditional parametric design method.https://www.mdpi.com/2075-1702/8/2/30product designmulti-way tree modelAHPTOPSISlearning-to-rank |
| spellingShingle | Boyang Chen Xiaobing Hu Yunliang Huo Xi Deng Research on Recommendation Method of Product Design Scheme Based on Multi-Way Tree and Learning-to-Rank Machines product design multi-way tree model AHP TOPSIS learning-to-rank |
| title | Research on Recommendation Method of Product Design Scheme Based on Multi-Way Tree and Learning-to-Rank |
| title_full | Research on Recommendation Method of Product Design Scheme Based on Multi-Way Tree and Learning-to-Rank |
| title_fullStr | Research on Recommendation Method of Product Design Scheme Based on Multi-Way Tree and Learning-to-Rank |
| title_full_unstemmed | Research on Recommendation Method of Product Design Scheme Based on Multi-Way Tree and Learning-to-Rank |
| title_short | Research on Recommendation Method of Product Design Scheme Based on Multi-Way Tree and Learning-to-Rank |
| title_sort | research on recommendation method of product design scheme based on multi way tree and learning to rank |
| topic | product design multi-way tree model AHP TOPSIS learning-to-rank |
| url | https://www.mdpi.com/2075-1702/8/2/30 |
| work_keys_str_mv | AT boyangchen researchonrecommendationmethodofproductdesignschemebasedonmultiwaytreeandlearningtorank AT xiaobinghu researchonrecommendationmethodofproductdesignschemebasedonmultiwaytreeandlearningtorank AT yunlianghuo researchonrecommendationmethodofproductdesignschemebasedonmultiwaytreeandlearningtorank AT xideng researchonrecommendationmethodofproductdesignschemebasedonmultiwaytreeandlearningtorank |