首页    期刊浏览 2026年01月03日 星期六
登录注册

文章基本信息

  • 标题:Identification of Patterns in Genetic-Algorithm-Based Solutions for Optimization of Process-Planning Problems Using a Data Mining Tool
  • 本地全文:下载
  • 作者:Sreeramulu, Dowluru
  • 期刊名称:International Journal of Applied Management and Technology
  • 出版年度:2012
  • 卷号:10
  • 期号:1
  • 页码:2
  • 出版社:Walden University
  • 摘要:This paper presents a novel use of data mining algorithms for extraction of knowledge from a set of process plans. The purpose of this paper is to apply data mining methodologies to explore the patterns in data generated by genetic-algorithm-generating process plans and to develop a rule set planner, which helps to make decisions in odd circumstances. Genetic algorithms are random-search algorithms based on the mechanics of genetics and natural selection. Because of genetic inheritance, the characteristics of the survivors after several generations should be similar. The solutions of a genetic algorithms for process planning consists of the operation sequence of a job, the machine on which each operation is performed, the tool used for performing each operation, and the tool approach direction. Among the optimal or near-optimal solutions, similar relationships may exist between the characteristics of the operation and sequential order. Data mining software known as See5 has been used to explore the relationship between the operation’s sequence and its attributes, and a set of rules has been developed. These rules can predict the positions of operations in the sequence of process planning.
  • 关键词:data mining; genetic algorithms; process planning
国家哲学社会科学文献中心版权所有