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Two evolutionary approaches to cross-clustering problems

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4 Author(s)
H. Luchian ; Fac. of Comput. Sci., Iasi Univ., Romania ; B. Paechter ; V. Radulescu ; S. Luchian

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 quasi-random 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

Published in:

Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on  (Volume:2 )

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