The Application of Improved Genetic Algorithm in Gate Location Optimization of Plastic Injection Molding

被引：0
|
作者：
Chen Xi [1 ]
Wang Xi-cheng [1 ]
机构：
[1] Univ Sci & Technol Liaoning, Sch Mech Engn & Automat, Anshan 114051, Liaoning, Peoples R China
来源：
MANUFACTURING PROCESS AND EQUIPMENT, PTS 1-4 | 2013年 / 694-697卷
基金：
中国国家自然科学基金;
关键词：
Genetic algorithm; Species equation; Kriging operator; Gate location design; Optimization;
D O I：
10.4028/www.scientific.net/AMR.694-697.2721
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A multi-population genetic algorithm based on species equation and Kriging operator is presented in this paper. The parameters of species equation are considered as design variables and processed by real coding, the equation is regarded as modified arithmetic crossover operator to participate in genetic operation. The Kriging operator is bought in to enhance the ability of search optimal solution and promote convergence. The improved genetic algorithm, combined with Z-MOLD simulation program, is used to search the optimal gate location. The results show that the algorithm can effectively solve the plastic injection molding problem.
引用
收藏
页码：2721 / +
页数：2
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