Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Агентно-событийное дискретно-событийное моделирование× | Метод Монте-Карло× | |
|---|---|---|
| Область≠ | Имитационное моделирование | Принятие решений |
| Семейство≠ | Process / pipeline | MCDM |
| Год появления≠ | 2000s | 1949 |
| Автор метода≠ | Hybridization formalized by multiple authors; Siebers & Aickelin, Lagergren & Buckley among key contributors | Metropolis, N., Ulam, S. |
| Тип≠ | Hybrid simulation paradigm | Robustness wrapper — Monte Carlo uncertainty propagation |
| Основополагающий источник≠ | Lagergren, J. H., & Buckley, E. (2010). A hybrid approach to simulation: Combining agent-based and discrete event simulation. Proceedings of the 2010 Winter Simulation Conference, pp. 170–181. IEEE. link ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| Другие названия≠ | AB-DES, Hybrid ABM-DES, Agent-DES, Hybrid Agent-Based Discrete-Event Simulation | — |
| Связанные≠ | 4 | 0 |
| Сводка≠ | Agent-based discrete-event simulation (AB-DES) is a hybrid modeling paradigm that couples autonomous agent behavior with an event-driven execution engine. It captures the decision-making heterogeneity of individual entities while maintaining the precise, time-stamped flow control of discrete-event simulation, making it suitable for complex systems where both individual agency and process sequencing matter. | MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGateНабор данных ↗ |
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