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確率的待ち行列シミュレーション×モンテカルロシミュレーション×
分野シミュレーション意思決定
系統Process / pipelineMCDM
提唱年19531949
提唱者Kendall, D. G.Metropolis, N., Ulam, S.
種類Stochastic simulation — waiting-line system analysisRobustness wrapper — Monte Carlo uncertainty propagation
原典Kendall, D. G. (1953). Stochastic processes occurring in the theory of queues and their analysis by the method of the imbedded Markov chain. The Annals of Mathematical Statistics, 24(3), 338–354. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
別名SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation
関連60
概要Stochastic Queueing Simulation models waiting-line systems where arrival and service processes follow probability distributions rather than fixed rates. By simulating thousands of random events, it estimates performance measures — mean waiting time, queue length, server utilization — under realistic uncertainty, making it the standard tool for designing and evaluating service systems from hospitals to call centers.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手法を比較: Stochastic Queueing Simulation · MONTE-CARLO-SIMULATION. 2026-06-15に以下より取得 https://scholargate.app/ja/compare