Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Diskreetti tapahtumasimulaatio (DES)× | Agenttipohjainen mallinnus (ABM)× | |
|---|---|---|
| Tieteenala | Simulointi | Simulointi |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1960s (formalized); modern computational form from 1970s onward | 1970s–1990s (formalized as a field) |
| Kehittäjä≠ | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) | Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s) |
| Tyyppi≠ | Stochastic process simulation | Computational simulation method |
| Alkuperäislähde≠ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 | Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press. DOI ↗ |
| Rinnakkaisnimet≠ | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) | ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling |
| Liittyvät≠ | 4 | 5 |
| Tiivistelmä≠ | 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. | Agent-based modeling (ABM) is a computational simulation method, formalized through the work of Thomas Schelling and Robert Axelrod in the 1970s–1990s, that simulates the behavior of complex systems by specifying and running autonomous agents — individuals, firms, cells, or any bounded entity — whose local interactions with each other and with their environment collectively produce global, system-level patterns that could not be predicted from any single agent's rules alone. |
| ScholarGateAineisto ↗ |
|
|