Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Моделирование сценариев политики в системах массового обслуживания× | Стохастическое моделирование очередей× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1909 (queueing theory); scenario application from 1960s–1970s OR literature | 1953 |
| Автор метода≠ | Erlang, A. K. (foundation); generalized by operations research community | Kendall, D. G. |
| Тип≠ | Comparative simulation experiment | Stochastic simulation — waiting-line system analysis |
| Основополагающий источник≠ | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 | Kendall, D. G. (1953). Stochastic processes occurring in the theory of queues and their analysis by the method of the imbedded Markov chain. The Annals of Mathematical Statistics, 24(3), 338–354. DOI ↗ |
| Другие названия | PSQS, policy queueing analysis, queueing policy comparison, scenario-based queueing model | SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation |
| Связанные≠ | 5 | 6 |
| Сводка≠ | Policy Scenario Queueing Simulation applies queueing theory and discrete-event simulation to evaluate two or more competing service or resource-allocation policies under realistic demand and capacity conditions. By holding the system structure constant and varying only the policy rules, analysts can directly compare throughput, waiting times, utilization, and equity outcomes before committing to real-world implementation. | Stochastic Queueing Simulation models waiting-line systems where arrival and service processes follow probability distributions rather than fixed rates. By simulating thousands of random events, it estimates performance measures — mean waiting time, queue length, server utilization — under realistic uncertainty, making it the standard tool for designing and evaluating service systems from hospitals to call centers. |
| ScholarGateНабор данных ↗ |
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