Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Simularea Stocastică a Cozilor× | Simularea Cozilor× | |
|---|---|---|
| Domeniu | Simulare | Simulare |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1953 | 1909 |
| Autorul original≠ | Kendall, D. G. | Agner Krarup Erlang |
| Tip≠ | Stochastic simulation — waiting-line system analysis | Stochastic simulation / analytical modeling |
| Sursa seminală≠ | 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 ↗ | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 |
| Denumiri alternative | SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue |
| Înrudite | 6 | 6 |
| Rezumat≠ | 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. | Queueing Simulation combines classical queueing theory with discrete-event simulation to model systems where entities arrive, wait for service, and depart. It predicts performance metrics such as average waiting time, queue length, and server utilization, enabling capacity planning and bottleneck identification across service, manufacturing, healthcare, and network systems. |
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