Research Output

Two evolutionary approaches to cross-clustering problems.

  Cross-clustering asks for a Boolean matrix to
be brought to a quasi-canonical form. The problem has
many applications in image processing, circuit design,
archaeology, ecology etc. The heuristics currently used
to solve it rely on either topological sorting or quasirandom
search. We present here two evolutionary
approaches to this problem: a permutation-based
solution and a clustering one. The results on both real
data and randomly generated, scalable, test data show
very good convergence and encouraging efficiency
properties, mainly for our second approach.

  • Type:

    Book Chapter

  • Date:

    30 November 1998

  • Publication Status:

    Published

  • Publisher

    IEEE

  • DOI:

    10.1109/CEC.1999.782514

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    006.3 Artificial intelligence

Citation

Luchian, H., Paechter, B., Radulescu, V. & Luchian, S. (1998). Two evolutionary approaches to cross-clustering problems. In Proceedings of the 1999 Congress on Evolutionary Computation, 860-870. IEEE. doi:10.1109/CEC.1999.782514. ISBN 0-7803-5536-9

Authors

Keywords

Cross-clustering; topological sorting; quasirandom search; permutation-based solution; clustering;

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