Application of Genetic Algorithms for Cutting Parameter Optimization

摘要：

Genetic Algorithms (GAs) represent a particular class of evolutionary algorithms that make use of techniques motivated by evolutionary biology. They have found applications in mathematics, physics, chemistry, economics, engineering and other fields. This paper addresses multi-pass turning optimization problem for minimum unit production cost Optimal cutting parameters including cutting speed, feed rate, and depth of cut are solved by a solution procedure using GAs. A machining example is given to illustrate the solution process. The effects of GA operators such as crossover and mutation are studied and the suitable values of crossover and mutation rates for the problem studied in this paper are recommended.

关键词： Genetic Algorithms cutting parameter optimization production cost crossover mutation

作者: Hong Zhang Peiqing Yang Libao An

作者单位: College of Life Sciences, Hebei United University Tangshan, China College of Life Sciences,Hebei United University Tangshan, China College of Mechanical Engineering Hebei United University Tangshan, China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Engineering and Applications(2011第三届计算机工程与应用国际会议 ICCEA2011)

会议地点: 海口

会议语种:英文

页码: 414-418

在线出版日期: 2011-07-15（万方平台首次上网日期，不代表论文的发表时间）