Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Агентное микромоделирование× | Имитационное моделирование дискретных событий (DES)× | |
|---|---|---|
| Область | Имитационное моделирование | Имитационное моделирование |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1957 (microsimulation); 2000s (hybrid ABMS) | 1960s (formalized); modern computational form from 1970s onward |
| Автор метода≠ | Orcutt, G. H. (microsimulation roots); Bonabeau, E. and others (ABM integration) | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Тип≠ | Hybrid simulation | Stochastic process simulation |
| Основополагающий источник≠ | Birkin, M., & Clarke, M. (2012). The enhancement of spatial microsimulation models using geodemographics. Annals of Regional Science, 49(2), 515–532. DOI ↗ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| Другие названия≠ | ABMS, Agent-Based Micro-Simulation, Microsimulation with Agent-Based Modeling, Hybrid ABM-Microsimulation | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Связанные≠ | 5 | 4 |
| Сводка≠ | Agent-based microsimulation (ABMS) merges traditional microsimulation's individual-level statistical tracking with agent-based modeling's behavioral rules and interaction mechanisms. It creates virtual populations of heterogeneous agents who evolve over time according to transition probabilities, adaptive behaviors, and social interactions, producing emergent system-level outcomes from micro-level dynamics. | 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. |
| ScholarGateНабор данных ↗ |
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