Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Дискретно-събитийна симулация (DES)× | Опашка M/M/c: Модел на опашка с множество сървъри× | |
|---|---|---|
| Област≠ | Симулационно моделиране | Изследване на операциите |
| Семейство≠ | Process / pipeline | Regression model |
| Година на възникване≠ | 1960s (formalized); modern computational form from 1970s onward | 1998 |
| Създател≠ | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) | Queueing-theory tradition; Gross & Harris |
| Тип≠ | Stochastic process simulation | Multi-server Markovian queueing model |
| Основополагащ източник≠ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 | Gross, D., & Harris, C. M. (1998). Fundamentals of Queueing Theory (3rd ed.). Wiley. ISBN: 978-0-471-17083-9 |
| Други названия≠ | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) | Multi-Server Erlang Queue, c-Server Markovian Queue, Erlang-C Queue, Çok Sunuculu M/M/c Kuyruğu |
| Свързани≠ | 4 | 3 |
| Резюме≠ | Discrete-Event Simulation (DES) is a computational modeling paradigm in which the state of a system changes only at a countable sequence of points in time — the events. Between events nothing changes, so the simulation clock jumps directly from one event to the next. Formalized through the foundational textbooks of Banks, Carson, Nelson and Nicol and of Law in the 1960s–2000s, DES has become the standard tool for analyzing queuing systems, healthcare patient flows, manufacturing lines, and logistics networks where entities move through resources over time. | The M/M/c queue is a multi-server stochastic model in which customers arrive according to a Poisson process at rate λ, are served by c identical servers each with exponentially distributed service times at rate μ, and wait in a single common queue when all servers are busy. Systematized within classical queueing theory and thoroughly treated by Gross and Harris (1998), it extends the simpler M/M/1 model to settings with parallel servers, making it the foundational tool for capacity planning in service systems. |
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