Abstract
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.
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© 1994 Springer-Verlag Berlin Heidelberg
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Schlierkamp-Voosen, D., Mühlenbein, H. (1994). Strategy adaptation by competing subpopulations. In: Davidor, Y., Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature — PPSN III. PPSN 1994. Lecture Notes in Computer Science, vol 866. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58484-6_264
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DOI: https://doi.org/10.1007/3-540-58484-6_264
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