Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Politikas scenāriju rindu simulācija× | Stohastiskā rindošanas simulācija× | |
|---|---|---|
| Nozare | Simulācija | Simulācija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 1909 (queueing theory); scenario application from 1960s–1970s OR literature | 1953 |
| Autors≠ | Erlang, A. K. (foundation); generalized by operations research community | Kendall, D. G. |
| Tips≠ | Comparative simulation experiment | Stochastic simulation — waiting-line system analysis |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi | PSQS, policy queueing analysis, queueing policy comparison, scenario-based queueing model | SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation |
| Saistītās≠ | 5 | 6 |
| Kopsavilkums≠ | 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. |
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