Methoden vergleichen

	Warteschlangensimulation	Agentenbasiertes Modellieren (ABM)
Fachgebiet	Simulation	Simulation
Familie	Process / pipeline	Process / pipeline
Entstehungsjahr	1909	1970s–1990s (formalized as a field)
Urheber	Agner Krarup Erlang	Thomas Schelling and Robert Axelrod (foundational contributions, 1970s–1990s)
Typ	Stochastic simulation / analytical modeling	Computational simulation method
Wegweisende Quelle	Kleinrock, L. (1975). Queueing Systems, Volume 1: Theory. Wiley-Interscience, New York. ISBN: 978-0471491101	Axelrod, R. (1997). The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton University Press.
Aliasnamen	Queue Simulation, Queuing Theory Simulation, Waiting-Line Simulation, DES-Queue	ABM, Ajan Tabanlı Modelleme (ABM), multi-agent simulation, individual-based modeling
Verwandt	6	5
Zusammenfassung	Queueing Simulation combines classical queueing theory with discrete-event simulation to model systems where entities arrive, wait for service, and depart. It predicts performance metrics such as average waiting time, queue length, and server utilization, enabling capacity planning and bottleneck identification across service, manufacturing, healthcare, and network systems.	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.