Apply what we have learned in Chapter 5 to explore validation issues for your simulation project.  This means you must:

• Carefully define issues to be investigated.
• Define measures of performance for evaluation.
• Describe manner in which model is to be used.
• Give alternative system configurations of interest.
• Describe various possible levels of detail, and defend the level chosen.
• Describe which parameters, distributions or subsystems will have the greatest impact on the desired measures and defend your answer.
• Describe what information and data have been collected on the system of interest.
• Describe how that info and data are used to specify operating procedures and probability distributions for the random variables used in the model.
• What details capture the essence of the system?
• What sources (e.g., books, people, etc.) have you drawn on for details of the operation of the system?
• How did you assess the adequacy of the probability distributions specified for generating input random variates?
• Describe how you selected your implementation framework (e.g., Matlab, mimlib, C, etc.).
• Describe how you mapped your simulation model onto the implementation and what you did to verify its correctness.
• Make some model runs and discuss at a high-level (i.e., no detailed output analysis) whether the output seems reasonable; what baseline tests did you develop (e.g., variety of settings of input parameters)?
• What batch trace options does your implementation have?
• What interactive trace options does your implementation have?
• How much difficulty would be involved in animating your simulation?
• What assumptions have been made about this simulation model?