This article proposes a model for analyzing nonstationary random processes using simulation methods, indicating potential applications in optimization problems.
This article proposes an approach to solving optimization problems where adequate estimates of the functional under study can only be obtained using simulation models of the systems under consideration. Such models include queueing network models with complex topological structures and probabilistic service time formalizations with general distribution laws. In these cases, analytical models cannot provide adequate calculation results for various model parameterizations.
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Stroganov et al. (2026) studied this question.
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