Input modeling
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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
Input modeling
- 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.