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Многокритериална дискретно-събитийна симулация×Монте Карло симулация×
ОбластСимулационно моделиранеВземане на решения
СемействоProcess / pipelineMCDM
Година на възникване1990s–2000s1949
СъздателVarious (DES: Tocher 1963; multi-objective integration: 1990s–2000s OR literature)Metropolis, N., Ulam, S.
ТипSimulation-optimization hybridRobustness wrapper — Monte Carlo uncertainty propagation
Основополагащ източникKleijnen, J. P. C., & Gaury, E. (2003). Short-term robustness of production management systems: A case study. European Journal of Operational Research, 148(2), 452–465. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Други названияMO-DES, Multi-objective DES, Pareto-based discrete-event simulation, DES with multi-objective optimization
Свързани50
РезюмеMulti-Objective Discrete-Event Simulation (MO-DES) couples a discrete-event simulation engine with multi-objective optimization to explore trade-offs among two or more conflicting performance measures — such as throughput, cost, and waiting time — across stochastic, time-ordered process models. It is widely applied in manufacturing, logistics, healthcare, and service system design.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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  3. PUBLISHED

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ScholarGateСравнение на методи: Multi-objective discrete-event simulation · MONTE-CARLO-SIMULATION. Извлечено на 2026-06-17 от https://scholargate.app/bg/compare