摘要
Travelling Salesman Problem(TSP) is a classical optimization problem and it is one of a class of NP-Problem.The purposes of this work is to apply data mining methodologies to explore the patterns in data generated by an Ant Colony Algorithm(ACA) performing a searching operation and to develop a rule set searcher which approximates the ACA′s searcher.An attribute-oriented induction methodology was used to explore the relationship between an operations′ sequence and its attributes and a set of rules has been developed.At the end of this paper,the experimental results have shown that the proposed approach has good performance with respect to the quality of solution and the speed of computation.
Travelling Salesman Problem （TSP） is a classical optimization problem and it is one of a class of NP- Problem. The purposes of this work is to apply data mining methodologies to explore the patterns in data generated by an Ant Colony Algorithm （ACA） performing a searching operation and to develop a rule set searcher which approximates the ACA＇s searcher. An attribute - oriented induction methodology was used to explore the relationship between an operations＇ sequence and its attributes and a set of rules has been developed. At the end of this paper,the experimental results have shown that the proposed approach has good performance with respect to the quality of solution and the speed of computation.
出处
《现代电子技术》
2007年第5期117-119,共3页
Modern Electronics Technique
关键词
数据挖掘
数据管理系统
数据库
数据分析
data mining
Travelling salesman problem
ant colony algorithm
data management system
