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Agent-baseret simuleringsmodellering af køsystemer×Monte Carlo-simulering×
FagområdeSimuleringBeslutningstagning
FamilieProcess / pipelineMCDM
Oprindelsesår2000s1949
OphavspersonMacal, C. M. & North, M. J. (hybrid formalization); queueing theory rooted in Erlang (1909)Metropolis, N., Ulam, S.
TypeHybrid simulation — agent-based + queueingRobustness wrapper — Monte Carlo uncertainty propagation
Oprindelig kildeMacal, C. M., & North, M. J. (2010). Tutorial on agent-based modelling and simulation. Journal of Simulation, 4(3), 151–162. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
AliasserAB-QS, Agent-Based Queue Simulation, ABM Queueing, Agent Queue Simulation
Relaterede50
ResuméAgent-Based Queueing Simulation (AB-QS) combines agent-based modeling with queueing theory to simulate systems where autonomous, decision-making entities interact through waiting lines and service points. Each entity (patient, customer, job) is modeled as an independent agent with its own state and behavioral rules, enabling richer, more realistic dynamics than classical queueing models alone.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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ScholarGateSammenlign metoder: Agent-based queueing simulation · MONTE-CARLO-SIMULATION. Hentet 2026-06-15 fra https://scholargate.app/da/compare