trait
Breeding[Chromosome, Global] extends (Vec[(Chromosome, Double, Boolean)], Global, Random) ⇒ Vec[Chromosome]
Abstract Value Members
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abstract
def
apply(v1: Vec[(Chromosome, Double, Boolean)], v2: Global, v3: Random): Vec[Chromosome]
Concrete Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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def
curried: (Vec[(Chromosome, Double, Boolean)]) ⇒ (Global) ⇒ (Random) ⇒ Vec[Chromosome]
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
tupled: ((Vec[(Chromosome, Double, Boolean)], Global, Random)) ⇒ Vec[Chromosome]
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Inherited from (Vec[(Chromosome, Double, Boolean)], Global, Random) ⇒ Vec[Chromosome]
Inherited from AnyRef
Inherited from Any
The breeding algorithm is given the current genome (selected and unselected chromosomes), along with their fitness values and selection flag (
true
meaning a chromosome was selected by the selection algorithm). It must return a new genome the population size of which should match the input genome.