Self-Adaptive Genetic Algorithm for Clustering

نویسندگان

  • Juha Kivijärvi
  • Pasi Fränti
  • Olli Nevalainen
چکیده

Clustering is a hard combinatorial problem which has many applications in science and practice. Genetic algorithms (GAs) have turned out to be very effective in solving the clustering problem. However, GAs have many parameters, the optimal selection of which depends on the problem instance. We introduce a new self-adaptive GA that finds the parameter setup on-line during the execution of the algorithm. In this way, the algorithm is able to find the most suitable combination of the available components. The method is robust and achieves results comparable to or better than a carefully fine-tuned non-adaptive GA.

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عنوان ژورنال:
  • J. Heuristics

دوره 9  شماره 

صفحات  -

تاریخ انتشار 2003