Package jline.api.pfqn.mva

Class Pfqn_qdKt

  • All Implemented Interfaces:
    
public final class Pfqn_qdKt

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      Modifier and Type Class Description

    • Field Summary

      Fields 
      Modifier and Type Field Description

    • Constructor Summary

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    • Constructor Detail

    • Method Detail

      • pfqn_qd

        @JvmOverloads() final static Ret.pfqnQd pfqn_qd(Matrix L, Matrix N, GammaFunction ga, BetaFunction be, Matrix Q0)

        Queue-Dependent (QD) approximate MVA solver

        Parameters:
        L -

        • the service demand matrix (M x R)

        N -

        • the population vector (1 x R)

        ga -

        • gamma scaling function (default: ones)

        be -

        • beta scaling function (default: ones)

        Q0 -

        • initial queue length estimate (M x R), null for proportional initialization

        Returns:

        • queue lengths Q, throughput X, utilization U, and iteration count

      • pfqn_qd

        @JvmOverloads() final static Ret.pfqnQd pfqn_qd(Matrix L, Matrix N, GammaFunction ga, BetaFunction be)

        Queue-Dependent (QD) approximate MVA solver

        Parameters:
        L -

        • the service demand matrix (M x R)

        N -

        • the population vector (1 x R)

        ga -

        • gamma scaling function (default: ones)

        be -

        • beta scaling function (default: ones)

        Returns:

        • queue lengths Q, throughput X, utilization U, and iteration count

      • pfqn_qd

        @JvmOverloads() final static Ret.pfqnQd pfqn_qd(Matrix L, Matrix N, GammaFunction ga)

        Queue-Dependent (QD) approximate MVA solver

        Parameters:
        L -

        • the service demand matrix (M x R)

        N -

        • the population vector (1 x R)

        ga -

        • gamma scaling function (default: ones)

        Returns:

        • queue lengths Q, throughput X, utilization U, and iteration count

      • pfqn_qd

        @JvmOverloads() final static Ret.pfqnQd pfqn_qd(Matrix L, Matrix N)

        Queue-Dependent (QD) approximate MVA solver

        Parameters:
        L -

        • the service demand matrix (M x R)

        N -

        • the population vector (1 x R)

        Returns:

        • queue lengths Q, throughput X, utilization U, and iteration count