Abstract
In this paper, modified versions of the classical deterministic maximum flow and minimum cost network flow problems are presented in a stochastic queueing environment. In the maximum flow network model, the throughput rate in the network is maximized such that for each arc of the network the resulting probability of finding congestion along that arc in excess of a desirable threshold does not exceed an acceptable value. In the minimum cost network flow model, the minimum cost routing of a flow of given magnitude is determined under the same type of constraints on the arcs. After proper transformations, these models are solved by Ford and Fulkerson's labeling algorithm and out-of-kilter algorithm, respectively.
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