Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Simulation à événements discrets basée sur des agents× | Simulation de Monte-Carlo× | |
|---|---|---|
| Domaine≠ | Simulation | Prise de décision |
| Famille≠ | Process / pipeline | MCDM |
| Année d'origine≠ | 2000s | 1949 |
| Auteur d'origine≠ | Hybridization formalized by multiple authors; Siebers & Aickelin, Lagergren & Buckley among key contributors | Metropolis, N., Ulam, S. |
| Type≠ | Hybrid simulation paradigm | Robustness wrapper — Monte Carlo uncertainty propagation |
| Source fondatrice≠ | 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 ↗ |
| Alias≠ | AB-DES, Hybrid ABM-DES, Agent-DES, Hybrid Agent-Based Discrete-Event Simulation | — |
| Apparentées≠ | 4 | 0 |
| Résumé≠ | 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. |
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