A review of terms you learned throughout this course.
empty-and-idle state
simulation
"progress" of a simulation study
discrete-event simulation
analytic vs. numerical models
simulation vs. analytical solution
physical vs. analog vs. abstract models
deterministic vs. stochastic models
deterministic vs. stochastic simulation
dynamic vs. static models
dynamic vs. static simulation
Monte Carlo sampling/Monte Carlo simulation
model
types of models:
physical
scale
analog
schematic
management game
analytic
mathematical
numeric
heuristic
abstract
Black Box model
abstraction
model verification
model validation
face validity
I/O transformations
simulation model
queueing system
M/M/1 queueing system
simulation of queuing systems
terminating system
terminating simulation
steady-state system
steady-state simulation
parameter
interarrival time
Poisson arrivals
exponential service times
system performance measure
input data distribution
simulation programming language
goodness-of-fit test
random numbers
pseudorandom numbers
random number streams
simulation clock
utilization of server
entities, attributes, resources, queues
state variable
event
process
fixed time advance method vs. next-event time advance
timing routine
time dependent statistics
modeling random phenomena in simulation
replications
batch means
initial conditions
empty-and-idle
initialization bias
warm up period
variance reduction techniques
common random numbers
antithetic variates
run length / sample size
experimental design in simulation
internal validity
external validity
metamodel
generalizability