Σύγκριση μεθόδων

	Προσομοίωση Στοχαστικών Ουρών	Προσομοίωση Monte Carlo
Πεδίο	Προσομοίωση	Λήψη Αποφάσεων
Οικογένεια	Process / pipeline	MCDM
Έτος προέλευσης	1953	1949
Δημιουργός	Kendall, D. G.	Metropolis, N., Ulam, S.
Τύπος	Stochastic simulation — waiting-line system analysis	Robustness wrapper — Monte Carlo uncertainty propagation
Θεμελιώδης πηγή	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.	Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association
Εναλλακτικές ονομασίες	SQS, Probabilistic Queueing Simulation, Stochastic Queue Modeling, Random Queueing Simulation	—
Συναφείς	6	0
Σύνοψη	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.