ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

エージェントベース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2000s1949
提唱者Macal, C. M. & North, M. J. (hybrid formalization); queueing theory rooted in Erlang (1909)Metropolis, N., Ulam, S.
種類Hybrid simulation — agent-based + queueingRobustness wrapper — Monte Carlo uncertainty propagation
原典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 ↗
別名AB-QS, Agent-Based Queue Simulation, ABM Queueing, Agent Queue Simulation
関連50
概要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.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 1 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Agent-based queueing simulation · MONTE-CARLO-SIMULATION. 2026-06-15に以下より取得 https://scholargate.app/ja/compare