class
Hungarian extends AnyRef
Instance Constructors
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new
Hungarian(cost: MatrixD)
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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def
getClass(): Class[_]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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ne(arg0: AnyRef): Boolean
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notify(): Unit
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notifyAll(): Unit
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synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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wait(): Unit
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def
wait(arg0: Long, arg1: Int): Unit
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def
wait(arg0: Long): Unit
Inherited from AnyRef
Inherited from Any
This is an O(n^3) implementation of the Hungarian algorithm (or Kuhn-Munkres algorithm). Find the maximum cost set of pairings between m x-nodes (workers) and n y-nodes (jobs) such that each worker is assigned to one job and each job has at most one worker assigned. It solves the maximum-weighted bipartite graph matching problem.
maximize sum i = 0 .. m-1 { cost(x_i, y_i) }
Caveat: only works if m <= n (i.e., there is at least one job for every worker).