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achieved best by SDD. GLEAM cannot compensate
flaws in the initial population within the runtime of
three minutes only.
The unexpected poor results of the new heuris-
tics are a motivation for us to change our focus to the
identification of suited local searchers that can assist
GLEAM. They are intended to improve the offspring
of a mating of the Evolutionary Algorithm. This con-
cept of hybridization was applied successfully to op-
timization tasks from the continuous parameter do-
main, as reported by (Jakob, 2006).
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