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基于代理的排队仿真×蒙特卡洛模拟×
领域仿真决策
方法族Process / pipelineMCDM
起源年份2000s1949
提出者Macal, C. M. & North, M. J. (hybrid formalization); queueing theory rooted in Erlang (1909)Metropolis, N., Ulam, S.
类型Hybrid simulation — agent-based + queueingRobustness wrapper — Monte Carlo uncertainty propagation
开创性文献Macal, 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 ↗
别名AB-QS, Agent-Based Queue Simulation, ABM Queueing, Agent Queue Simulation
相关50
摘要Agent-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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ScholarGate方法对比: Agent-based queueing simulation · MONTE-CARLO-SIMULATION. 于 2026-06-15 检索自 https://scholargate.app/zh/compare