A slippery genetic algorithm-based process mining system for achieving better quality assurance in the garment industry

作者：

Highlights：

• Provide knowledge support for quality assurance in the garment industry.

• Extract relationships among parameters and quality by fuzzy association rule mining.

• Design novel nature-inspired genetic algorithms with variable lengths.

• Optimize fuzzy association rules with the use of the slippery genetic algorithm.

摘要

•Provide knowledge support for quality assurance in the garment industry.•Extract relationships among parameters and quality by fuzzy association rule mining.•Design novel nature-inspired genetic algorithms with variable lengths.•Optimize fuzzy association rules with the use of the slippery genetic algorithm.

论文关键词：Genetic algorithm,Fuzzy association rule mining,Biological slippage,Quality assurance,Garment industry

论文评审过程：Received 10 February 2015, Revised 26 October 2015, Accepted 27 October 2015, Available online 30 October 2015, Version of Record 18 November 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.10.035