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Titlebook: Stochastic Programming; F. Archetti,G. Pillo,M. Lucertini Conference proceedings 1986 Springer-Verlag Berlin Heidelberg 1986 algorithms.co

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Iterative approximations for networks of queues,roduct-form. In such cases there are relatively elegant and simple computational procedures for the relevant behavioral characteristics. Quite commonly, however, the conditions are too severe and exact solution is practically impossible for larger problems..In this paper we will consider iterative a
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Convergence theories of distributed iterative processes: A survey,c information from the environment or other processors via communication links. Several applications in distributed optimization, parameter estimation, and communication networks are described. Issues of asymptotic convergence and agreement are explored under very weak assumptions on the ordering of
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Simulation for passage times in non-Markovian networks of queues,the jobs are used to construct point and interval estimates. Our results apply to networks with “single states” for passage times. Based on a single simulation run, the procedures provide point estimates and confidence intervals for characteristics of limiting passage times.
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Queue predictors for stochastic traffic flows control, paper, of bulk arrivals allows the controller to assume for the optimization larger unit time inte. vals with great advantage for on-line implementation. Besides, the introduction of estimated (rather than a priori known) arrival rates is a first step towards modelling and control of simple traffic networks.
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A probabilistic analysis of Monte Carlo algorithms for a class of counting problems,roblems (the Intersection Cardinality Problem, denoted as ICP) is considered, and tight bounds on its indeces of performance are derived. It is shown that, under mild assumptions on the parameters of the stochastic model of ICP, the average time of the algorithm is consistently less than its worst case time complexity.
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Convergence theories of distributed iterative processes: A survey,, and communication networks are described. Issues of asymptotic convergence and agreement are explored under very weak assumptions on the ordering of computations and the timing of information reception. Progress towards constructing a broadly applicable theory is surveyed.
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