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.