Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
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Application of Genetic and Local Optimization Algorithms for Object Clustering Problem with Similarity Coefficients

유사성 계수를 이용한 군집화 문제에서 유전자와 국부 최적화 알고리듬의 적용

  • Yim, Dong-Soon (Department of Industrial and Systems Engineeringm Hannam University) ;
  • Oh, Hyun-Seung (Department of Industrial and Systems Engineeringm Hannam University)
  • 임동순 (한남대학교 산업시스템공학) ;
  • 오현승 (한남대학교 산업시스템공학)
  • Published : 2003.03.31
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Abstract

Object clustering, which makes classification for a set of objects into a number of groups such that objects included in a group have similar characteristic and objects in different groups have dissimilar characteristic each other, has been exploited in diverse area such as information retrieval, data mining, group technology, etc. In this study, an object-clustering problem with similarity coefficients between objects is considered. At first, an evaluation function for the optimization problem is defined. Then, a genetic algorithm and local optimization technique based on heuristic method are proposed and used in order to obtain near optimal solutions. Solutions from the genetic algorithm are improved by local optimization techniques based on object relocation and cluster merging. Throughout extensive experiments, the validity and effectiveness of the proposed algorithms are tested.

Keywords

References

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