Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uigaji wa Matukio ya Sera za Msitari× | Uigaji wa Mfumo wa Kungoja× | |
|---|---|---|
| Nyanja | Uigaji | Uigaji |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1909 (queueing theory); scenario application from 1960s–1970s OR literature | 1909 |
| Mwanzilishi≠ | Erlang, A. K. (foundation); generalized by operations research community | Agner Krarup Erlang |
| Aina≠ | Comparative simulation experiment | Stochastic simulation / analytical modeling |
| Chanzo asilia | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 |
| Majina mbadala | PSQS, policy queueing analysis, queueing policy comparison, scenario-based queueing model | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue |
| Zinazohusiana≠ | 5 | 6 |
| Muhtasari≠ | 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. | 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. |
| ScholarGateSeti ya data ↗ |
|
|