This document discusses input modeling for simulation and outlines 4 steps: 1) Collect data from the real system or use expert opinion if data is unavailable 2) Identify a probability distribution to represent the input process 3) Choose parameters for the distribution family by estimating from the data 4) Evaluate the chosen distribution through goodness of fit tests or create an empirical distribution if none is found

1. Input Modeling
Chapter 10 (2nd
ed.)

2. 4 Steps to Input Modeling
1. Collect data from real system
 Substantial time and resources
 When data is unavailable (due to time
limit or no existing process):
• Use expert opinion
• Make educated guess based from
knowledge of the process

3. 4 Steps to Input Modeling
1. Identify probability distribution to
represent input process
 Develop frequency distribution or
histogram
 Choose a family of distributions

4. 4 Steps to Input Modeling
1. Choose the parameters of the
distribution family.
 These parameters are estimated from the
data.
2. Evaluate the chosen distribution and its
parameters.
 Goodness of fit test : chi-square or KS test.
 This is an iterative process of selecting and
rejecting the different distributions until the
desired is found.
 If none is found, create an empirical
distribution.

5. Data Collection Problems
 Inter-arrival times are not
homogenous
 Service times which are dependent
on other factors
 Service time termination
 Machine breakdowns

6. No DataNo Data
Old DataOld Data
Missing DataMissing Data
GuesstimatesGuesstimates
Erroneous DataErroneous Data
No resourceNo resource
Data Problems with
Simulation
SimplifyingSimplifying
assumptionsassumptions
Using AveragesUsing Averages
OutliersOutliers
Optimistic DataOptimistic Data
PoliticsPolitics

7. Bad data equals bad modelsBad data equals bad models
The Best models fail under badThe Best models fail under bad
datadata
Successful simulation is unlikelySuccessful simulation is unlikely
with bad datawith bad data
Consequence of Data Problems

8. Always question dataAlways question data
Electronic data does mean goodElectronic data does mean good
data.data.
Know the sourceKnow the source
Allocate sufficient time to collectAllocate sufficient time to collect
and analyze dataand analyze data
Guidelines in Data
Collection

9. Suggestions to facilitate
data collection:
1. Plan
 Collect data while pre-observing
 Create forms and be prepared to
modify them when needed
 Video tape is possible and extract date
later

10. Suggestions to facilitate
data collection:
1. Analyze.
 Determine if data is adequate.
 Do not collect superfluous data.
2. Try to combine homogenous data.
 Use two sample t-test.
3. Be wary of data censoring.
4. Look for relationships between variables
using a scatter plot.
5. Be aware of autocorrelations within a
sequence of observations.