Optimisation of multi-pass milling using genetic algorithm and genetic simulated annealing

被引：53
|
作者：
Wang, ZG [1 ]
Wong, YS [1 ]
Rahman, M [1 ]
机构：
[1] Natl Univ Singapore, Dept Mech & Prod Engn, Singapore 119260, Singapore
来源：
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | 2004年 / 24卷 / 9-10期
关键词：
genetic algorithm; genetic simulated annealing; milling;
D O I：
10.1007/s00170-003-1789-5
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The selection of optimal machining parameters plays an important part in computer-aided manufacturing. The optimisation of machining parameters is still the subject of many studies. Genetic algorithm (GA) and simulated annealing (SA) have been applied to many difficult combinatorial optimisation problems with certain strengths and weaknesses. In this paper, genetic simulated annealing (GSA), which is a hybrid of GA and SA, is used to determine optimal machining parameters for milling operations. For comparison, basic GA is also chosen as another optimisation method. An application example that has previously been solved using geometric programming (GP) method is presented. The results indicate that GSA is more efficient than GA and GP in the application of optimisation.
引用
收藏
页码：727 / 732
页数：6
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