Sargent (validation and verification) Flashcards
Why do validation:
In order to ensure that the model works for the intended purpose.
In problem structuring the purpose will often be to achieve clarity and to map interest and conflicting actions.
What is model verification according to Sargent (2013)?
Ensuring the computer programming and its implementation of the conceptual model are done correctly
What is model verification according to Sargent (2013)?
Ensuring the computer programming and its implementation of the conceptual model are done correctly
What is model validation according to Sargent (2013)?
Ensuring that the model serves it purpose
that a model works well and gives accurate results within its intended use.
What is model credibility according to Sargent (2013)?
Is concerned with developing confidence in the user, which is required to use the model and the derived information from the model
When is a model considered valid for experimental condition according to Sargent (2013)?
if the model’s accuracy falls within the desired range for its intended purpose, then it is considered acceptable.
Full validated model vs sufficient accuracy:
Often, we will not fully validate a model –> too costly.
Validate it to some extend. It will be sufficient accurate to the purpose of the model.
Doing more validation creating more confidence in the model also result in higher cost
The value of a model increases with the confidence in a model (validity) but at a decreasing rate
Three decision making approaches for deciding on simulation model validity (Sargent 2013)
All approached require the model development team to conduct verification and validation as part of the model development process
1) The model development team decide themselves if the model is valid
→ This is based on result of test and evaluations
2) The users of the simulation model is determining the validity of the model.
→ Better than above
→ Here the users are heavily part of the model development process when doing validation and verification
3) Use a third party to decide on the simulation models validity
→ Called an independent verification and validation (IV&V)
→ Often used when the model developed are very large
→ The IV&V team can conduct the validation during the development of model or after the model is developed.
- When done during the development team will not move on to the next stage before the IV&V team has evaluated it to satisfy the requirement for the current stage
- When done after the development of the model it is often extremely costly and time consuming
Explain the simplified version of the model development process (Sargent 1981):
Problem entity is the system or phenomena to be modelled
Conceptual model is the mathematical/logical/graphical representation of the problem
- Developed through analysis and modelling phase
Computerized model is the conceptual model implemented on a computer
- Developed through a computer programming and implementation phase
inferences about the problem entity are obtained by
conducting computer experiments on the computerized model in the experimentation phase.
Conceptual model validation is determining that theories and assumption underlying the conceptual model are correct and the model representation of the entity is reasonable for the intended purpose
Computerized model verification: Assuring that the computer programming and implementation of the conceptual model are correct
Operational validation determines that the models accuracy is within the range of accuracy for the models intended purpose
Data validity ensures that the data necessary for model building, model evaluation and test are adequate and correct
The process is iterative and every time any changes are made the process start over again
Animation as validation technic (Sargent 2013)
The model’s operational behavior is displayed graphically as the model moved trough time
For instant the movement of parts in a factory
Often not all behaviors being observed since it is often done in a short time interval
Comparison to other models as validation technic (Sargent 2013)
Various results of the simulation model is being validated by comparing it to results of other (valid) models
Data relationship correctness as validation technic (Sargent 2013)
Data relationship correctness validation ensures accurate and consistent connections between data elements in a model or system.
Degenerate tests as validation technic (Sargent 2013)
A test of the models behavior is done by appropriate selection of values of input and internal parameters.
For instant does the average number in the queue continue to increase over time, when the arrival rate is larger than the service rate ?
Event validity as validation technic (Sargent 2013)
The “events” of occurrences of the simulation model are compared to those of the real system to determine whether they are similar
For instant: compared the number of fires in the fire department simulation to the actual number of fires
Extreme condition test as validation technic (Sargent 2013)
The model structure and outputs should be plausible for any extreme and unlikely combination of levels of factors in the system
Face validity as validation technic (Sargent 2013)
Face validity is a subjective assessment of whether a model measures what it claims to measure based on its content and relevance.
For example is the logic in the conceptual model correct and are the models input-output relationship reasonable?
Historical data validation as validation technic (Sargent 2013)
If historical data exist, part of the data is used for build the model and remaining data are used to test whether the model behaves as the system does
Internal validity as validation technic (Sargent 2013)
Several replications (runs) of a stochastic model are made to determine the amount of (internal) stochastic variability in the model
If there are large variation in the results it might make the model and the results questionable
Operational graphics as validation technic (Sargent 2013)
Performance measure are shown graphically while the model is running through time
The performance measure could be number un queue or percentage og servers which are busy
Parameter variability-sensitivity analysis as validation technic (Sargent 2013)
Changing values and input or internal parameter of the model to determine the effect at the model´s behavior or output.
The same relationship should occur in the model as in the real system.
Predictive validation as validation technic (Sargent 2013)
The model predicts (forecast) the system´s behavior. A comparison is made between these to see if they are the same.
Conceptual model validation according to Sargent (2013)
1) The theories and assumptions for the conceptual model are correct → Mathematical analysis and statistical methods on problem entity data.
2) The model’s representation of the problem entity and the model’s structure is reasonable for the intended purpose of the model → Has the appropriate detail and aggregate level been used?
Primary validation techniques are
- Face validation, structured walkthrough and trace
Computerized model verification according to Sargent (2013)
Ensures that the computer programming and implementation of the conceptual model are correct
Improving the verification can be done by using a simulation language
Primary technics are Structured walkthroughs and trace
Approached for testing simulation software (Sargent 2013)(Fairly 1976)
Static testing: the computer program is analysed to see if it is correct
- Structured walkthrough, correctness proofs and examining the structure properties of the program
Dynamic testing: The computer program is executed under different conditions and the values obtained are used to decide if the program and its implementation are correct
- Trace, input-output relationships, data relationship correctness