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Correlational parameter tuning by genetic meta-algorithm

Kieś P., Kosiński W.

Control and Cybernetics

2000

Vol. 29, no 4

1031-1042

The general problem of an off-line parameter tuning in the Binary Genetic Algorithm (BGA) is introduced. An example of such a tuning: a class of Correlational Tuning Methods (CTMs) is proposed. The main idea of a CTM is that it uses a mapping called measurement function as an assessment of the BGA's effciency. An example of a measurement function is described and two examples of CTMs: a modified "trials and errors" method and a modified genetic meta-algoritlm (metaBGA) are shown. Finally, experimental results with the metaBGA for four kinds of test fitness functions, where the code permutation is the tuned parameter, are presented.