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Buzen's algorithm : ウィキペディア英語版
Buzen's algorithm
In queueing theory, a discipline within the mathematical theory of probability, Buzen's algorithm (or convolution algorithm) is an algorithm for calculating the normalization constant G(''N'') in the Gordon–Newell theorem. This method was first proposed by Jeffrey P. Buzen in 1973. Computing G(''N'') is required to compute the stationary probability distribution of a closed queueing network.
Performing a naïve computation of the normalising constant requires enumeration of all states. For a system with ''N'' jobs and ''M'' states there are \tbinom states. Buzen's algorithm "computes G(1), G(2), ..., G(''N'') using a total of ''NM'' multiplications and ''NM'' additions." This is a significant improvement and allows for computations to be performed with much larger networks.〔
==Problem setup==

Consider a closed queueing network with ''M'' service facilities and ''N'' circulating customers. Write ''n''''i''(''t'') for the number of customers present at the ''i''th facility at time ''t'', such that \scriptstyle \sum_^M n_i = N. We assume that the service time for a customer at the ''i''th facility is given by an exponentially distributed random variable with parameter ''μ''''i'' and that after completing service at the ''i''th facility a customer will proceed to the ''j''th facility with probability ''p''''ij''.〔
It follows from the Gordon–Newell theorem that the equilibrium distribution of this model is
::\mathbb P(n_1,n_2,\cdots,n_M) = \frac\prod_^M \left( X_i \right)^
where the ''X''''i'' are found by solving
::\mu_j X_j = \sum_^M \mu_i X_i p_\quad\textj=1,\ldots,M.
and ''G''(''N'') is a normalizing constant chosen that the above probabilities sum to 1.〔
Buzen's algorithm is an efficient method to compute G(''N'').〔

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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