Chapter 8 Analyzing Simulation Output
LEARNING OBJECTIVES
To be able to recognize the different types of statistical quantities used within and produced by simulation models
To be able to analyze finite horizon simulations via the method of replications
To be able to analyze infinite horizon simulations via the method of batch means and the method of replication-deletion
To be able to compare simulation alternatives and make valid decisions based on the statistical output of a simulation
Because the inputs to the simulation are random, the outputs from the simulation are also random. You can think of a simulation model as a function that maps inputs to outputs. This chapter presents the statistical analysis of the outputs from simulation models.
In addition, a number of issues that are related to the proper execution of simulation experiments are presented. For example, the simulation outputs are dependent upon the input random variables, input parameters, and the initial conditions of the model. Initial conditions refer to the starting conditions for the model, i.e. whether or not the system starts “empty and idle.” The effect of initial conditions on steady state simulations will be discussed in this chapter.
Input parameters are related to the controllable and uncontrollable factors associated with the system. For a simulation model, all input parameters are controllable; however, in the system being modeled we typically have control over only a limited set of parameters. Thus, in simulation you have the unique ability to control the random inputs into your model. This chapter will discuss how to take advantage of controlling the random inputs.
Input parameters can be further classified as decision variables. That is, those parameters of interest that you want to change in order to test model configurations for decision-making. The structure of the model itself may be considered a decision variable when you are trying to optimize the performance of the system. When you change the input parameters for the simulation model and then execute the simulation, you are simulating a different design alternative.
This chapter describes how to analyze the output from a single design alternative and how to analyze the results of multiple design alternatives. To begin the discussion you need to build an understanding of the types of statistical quantities that may be produced by a simulation experiment.