Bandingkan metode
Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.
| Simulasi Antrean× | Simulasi Kejadian Diskrit (DES)× | |
|---|---|---|
| Bidang | Simulasi | Simulasi |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 1909 | 1960s (formalized); modern computational form from 1970s onward |
| Pencetus≠ | Agner Krarup Erlang | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Tipe≠ | Stochastic simulation / analytical modeling | Stochastic process simulation |
| Sumber perintis≠ | Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101 | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| Alias≠ | Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Terkait≠ | 6 | 4 |
| Ringkasan≠ | 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. | 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. |
| ScholarGateSet data ↗ |
|
|