Strategy adaptation by competing subpopulations
The breeder genetic algorithm BGA depends on a set of control parameters and genetic operators. In this paper it is shown that strategy adaptation by competing subpopulations makes the BGA more robust and more efficient. Each subpopulation uses a different strategy which competes with other subpopulations. Numerical results are presented for a number of test functions.
Keywordsbreeder genetic algorithm strategy adaptation competition multiresolution search
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