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Simulasi Kejadian Diskrit Multi-Objektif×Simulasi Monte Carlo×
BidangSimulasiPengambilan Keputusan
KeluargaProcess / pipelineMCDM
Tahun asal1990s–2000s1949
PencetusVarious (DES: Tocher 1963; multi-objective integration: 1990s–2000s OR literature)Metropolis, N., Ulam, S.
TipeSimulation-optimization hybridRobustness wrapper — Monte Carlo uncertainty propagation
Sumber perintisKleijnen, 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 ↗
AliasMO-DES, Multi-objective DES, Pareto-based discrete-event simulation, DES with multi-objective optimization
Terkait50
RingkasanMulti-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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ScholarGateBandingkan metode: Multi-objective discrete-event simulation · MONTE-CARLO-SIMULATION. Diakses 2026-06-17 dari https://scholargate.app/id/compare