Multi-model machining path planning based on improved genetic algorithm

Weijun Lei, Xiaosheng Cheng, Ning Dai, Baosu Guo, Xiangjia Li

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

In order to increase the total machining efficiency in NC machining, multiple models are machined in a piece of blank frequently. To solve the machining path planning of multiple models, a method by adjusting the machining model and its connected points several times is presented. On the basis of simplifying the machining contour to the geometrical center of the machining model, genetic algorithm is adopted to plan the general machining route of the multiple models. On the situation of avoiding the interference between machining models, the posture and the start point of the machining model are transformed to shorten the machining length between adjacent models. To solve the problems of genetic algorithm premature and hard to jump out of local optimal solution, parent and child are set to participate in competition and adaptive genetic operators is adopted to improve the genetic algorithm. The experimental results show that this method can effectively minimize the overall processing length and the improved genetic algorithm has great convergence results.

Original languageEnglish (US)
Pages (from-to)153-161
Number of pages9
JournalJixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering
Volume50
Issue number11
DOIs
StatePublished - Jun 5 2014

Keywords

  • Genetic algorithm
  • Multi-model machining
  • Path planning

ASJC Scopus subject areas

  • Mechanical Engineering
  • Computer Science Applications
  • Applied Mathematics

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