Chapter 7 Advanced Event and Process View Modeling
LEARNING OBJECTIVES
To develop a deeper understanding of effective modeling with processes and resources.
To be able to model non-stationary arrivals using arrival schedules.
To be able to model the staffing/scheduling of resources using resource capacity schedules.
To be able to capture statistics over specific periods of time.
To be able to model balking and reneging within queuing situations.
To develop a deeper understanding of effective modeling with events.
To develop a basic understanding of verification and validation methods within simulation.
The primary purpose of this chapter is to dive deeper into more complex modeling situations that are commonly experienced within discrete-event dynamic systems. First we will explore how to use the KSL process view constructs to model the common situation of a station where work is performed. Because the KSL is built upon and can take advantage of the flow of control and data structures available within Kotlin, we will see that fairly complex systems can be readily modeled using the primitive elements discussed in the previous chapter. In addition, when modeling a system, there may be situations where there is limited waiting space for the entities to be processed or we need to maintain some distance between entities that wait (such as social distance requirements) This situation presents a number of interesting modeling possibilities. We will look at a way to use resources to handle this situation.
Many realistic modeling situations have non-stationary characteristics that require the generation of arrivals where the mean rate of arrival depends on the time, such as lunch hour at your favorite fast food restaurant. We will see how the KSL provides constructs for this situation. In addition, if the arrivals to a system vary with time, we may want to vary the capacity of the resources with respect to time. The KSL also provides some basic ways to address this situation. In addition, because the system performance can be non-stationary, we may want to collect statistics during specific intervals of time. The KSL has the ability to specify the collect of responses during specific intervals according to a schedule.
Lastly, the chapter will look at a few miscellaneous modeling situations that should help you to develop ideas for effective modeling of a variety of situations. We will start by looking more closely at processes and resources.
NOTE!
This chapter provides a series of example Kotlin code that illustrates the use of KSL constructs for implementing process and event view simulation models. The full source code of the examples can be found in the accompanying KSLExamples project associated with the KSL repository. The files for each example of this chapter can be found here.