Week 7

Question 1

what is output data analysis?

Answer 1

is the analysis of data generated by a simulation run to predict system performance or compare performance of two or more system designs.
- Output data from simulation is random
* Results may differ greatly from the true characteristics of the system
* Estimate a measure of performance of a simulated system
* Use a confidence interval

Question 2

what are the two types of simulations:

Answer 2

1. Terminating simulation: runs for a duration of time
   eg, bank (terminating event).
   - A terminating simulation is one in which the simulation starts at a defined state or time and ends when it reaches some other defined state or time.
2. Steady-state simulation: runs over a long period of time
   eg computer/telecom networks, climate
   - A steady-state simulation is used to investigate the steady-state behavior of a system, where the simulation continues until the system reaches a steady-state.

Question 3

what are the issues with output data analysis? 1

Answer 3

1. Initial / Starting Conditions: Initial observations may not be good estimations of the true conditions of the system, Transient/warm-up period where you either impose initial conditions or
   run simulation for a while and discard initial portion
   Eg
   * A heavily congested system manufacturing system

Question 4

what are the issues with output data analysis? 2

Answer 4

2. Auto-correlated / Dependent Data: Dependence between events, need to ensure independence
   - Classical statistical methods are not directly applicable.
   - A queuing system and the waiting time of a customer.
   - An inventory system and the amount of beginning inventory on a given day.

Question 5

how do we compare alternative system configurations?

Answer 5

• Output from several different simulation models that might represent competing system designs or alternative operating policies
• Very important as the real utility of simulation lies
  in comparing such alternatives before implementation in practice