Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Προσομοίωση Διακριτών Γεγονότων Βασισμένη σε Πράκτορες× | Διακριτή Προσομοίωση Γεγονότων (DES)× | |
|---|---|---|
| Πεδίο | Προσομοίωση | Προσομοίωση |
| Οικογένεια | Process / pipeline | Process / pipeline |
| Έτος προέλευσης≠ | 2000s | 1960s (formalized); modern computational form from 1970s onward |
| Δημιουργός≠ | Hybridization formalized by multiple authors; Siebers & Aickelin, Lagergren & Buckley among key contributors | Banks, Carson, Nelson & Nicol (textbook lineage); foundational work by Tocher & Conway (1960s) |
| Τύπος≠ | Hybrid simulation paradigm | Stochastic process simulation |
| Θεμελιώδης πηγή≠ | 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 ↗ | Banks, J., Carson, J.S., Nelson, B.L. & Nicol, D.M. (2010). Discrete-Event System Simulation (5th ed.). Pearson. ISBN: 978-0136062127 |
| Εναλλακτικές ονομασίες≠ | AB-DES, Hybrid ABM-DES, Agent-DES, Hybrid Agent-Based Discrete-Event Simulation | DES, event-driven simulation, Ayrık Olay Simülasyonu (DES) |
| Συναφείς | 4 | 4 |
| Σύνοψη≠ | 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. | 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. |
| ScholarGateΣύνολο δεδομένων ↗ |
|
|