MULTI-OBJECTIVE PERFORMANCE DESIGN OF INJECTION MOLDING MACHINE VIA A NEW MULTI-OBJECTIVE OPTIMIZATION ALGORITHM

被引:0
|
作者
Ding, Li-ping [1 ]
Tan, Jian-rong [2 ]
Wei, Zhe [2 ]
Chen, Wen-liang [1 ]
Gao, Zhan [3 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Dept Mech Engn, Nanjing 210016, Peoples R China
[2] Zhejiang Univ, Dept Mech Engn, Hangzhou 310027, Peoples R China
[3] Nantong Univ, Sch Comp Sci & Technol, Nantong 226019, Peoples R China
关键词
K means clustering; Support vector clustering; Multi-objectives optimization; Injection molding machine;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
To solve the multi-objective optimization problem of injection molding machine product's overall performance, firstly, the optimal design of injection molding machine is studied and the design problem is formulated as a constrained multi-objective problem involving continuous and discrete design variables. Furthermore, with the K means of joint support vector clustering method to reduce the number of external stocks, a new multi-objective optimization algorithm KSVC-SPEA is proposed. Then, taking the multi-objective optimization of the overall performance of the HT160X1N high-speed injection molding machine as an example, the traditional linear weighting methods, Strength Pareto Evolutionary Algorithm (SPEA) and the KSCV-SPEA are applied. Case studies show that the KSVC-SPEA is able to effectively achieve the multi-objective optimization design of the overall performance of injection molding machine with a high efficiency.
引用
收藏
页码:3939 / 3949
页数:11
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