Constructor Detail

Method Detail

• pfqn_harel_bounds

  @JvmOverloads() final static Ret.pfqnHarelBounds pfqn_harel_bounds(Matrix rho, Integer N, Double Z, Integer maxUB)

  Compute Harel et al. throughput bounds for a closed single-class queueing network.

  Parameters:

  rho - Loading vector (k x 1 matrix), where rho_i = x_i / mu_i (visit ratio divided by service rate for queue i)

  N - Number of customers in the closed network

  Z - Think time (must be zero; throws exception if nonzero)

  maxUB - Maximum n for upper bound computation (default: min(N, 7))

  Returns:

  Ret.pfqnHarelBounds containing LB, UB(n) for n=2..maxUB, and TH(n) values

• pfqn_harel_bounds

  @JvmOverloads() final static Ret.pfqnHarelBounds pfqn_harel_bounds(Matrix rho, Integer N, Double Z)

  Compute Harel et al. throughput bounds for a closed single-class queueing network.

  Parameters:

  rho - Loading vector (k x 1 matrix), where rho_i = x_i / mu_i (visit ratio divided by service rate for queue i)

  N - Number of customers in the closed network

  Z - Think time (must be zero; throws exception if nonzero)

  Returns:

  Ret.pfqnHarelBounds containing LB, UB(n) for n=2..maxUB, and TH(n) values

• pfqn_harel_bounds

  @JvmOverloads() final static Ret.pfqnHarelBounds pfqn_harel_bounds(Matrix rho, Integer N)

  Compute Harel et al. throughput bounds for a closed single-class queueing network.

  Parameters:

  rho - Loading vector (k x 1 matrix), where rho_i = x_i / mu_i (visit ratio divided by service rate for queue i)

  N - Number of customers in the closed network

  Returns:

  Ret.pfqnHarelBounds containing LB, UB(n) for n=2..maxUB, and TH(n) values

• pfqn_harel_lb

  @JvmOverloads() final static Double pfqn_harel_lb(Matrix rho, Integer N, Double Z)

  Compute only the lower bound LB (convenience function).

  Parameters:

  rho - Loading vector (k x 1 matrix)

  N - Number of customers

  Z - Think time (must be zero)

  Returns:

  Lower bound on throughput

• pfqn_harel_lb

  @JvmOverloads() final static Double pfqn_harel_lb(Matrix rho, Integer N)

  Compute only the lower bound LB (convenience function).

  Parameters:

  rho - Loading vector (k x 1 matrix)

  N - Number of customers

  Returns:

  Lower bound on throughput

• pfqn_harel_ub

  @JvmOverloads() final static Double pfqn_harel_ub(Matrix rho, Integer N, Integer n, Double Z)

  Compute a specific upper bound UB(n) (convenience function).

  Parameters:

  rho - Loading vector (k x 1 matrix)

  N - Number of customers

  n - The n value for UB(n), must be 2 <= n <= min(N, 7)

  Z - Think time (must be zero)

  Returns:

  Upper bound UB(n) on throughput

• pfqn_harel_ub

  @JvmOverloads() final static Double pfqn_harel_ub(Matrix rho, Integer N, Integer n)

  Compute a specific upper bound UB(n) (convenience function).

  Parameters:

  rho - Loading vector (k x 1 matrix)

  N - Number of customers

  n - The n value for UB(n), must be 2 <= n <= min(N, 7)

  Returns:

  Upper bound UB(n) on throughput