Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Simularea Cozilor× | Simularea Stocastică a Cozilor× | |
|---|---|---|
| Domeniu | Simulare | Simulare |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1909 | 1953 |
| Autorul original≠ | Agner Krarup Erlang | Kendall, D. G. |
| Tip≠ | Stochastic simulation / analytical modeling | Stochastic simulation — waiting-line system analysis |
| Sursa seminală≠ | 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 ↗ |
| Denumiri alternative | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue | SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation |
| Înrudite | 6 | 6 |
| Rezumat≠ | 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. | 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. |
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