Chapter 6 Modeling Systems with Advanced Process Concepts
LEARNING OBJECTIVES
To be able to model non-stationary arrivals using arrival schedules.
To be able to model the staffing/scheduling and failure/repair of resources using resource capacity schedules and failures.
To be able to capture statistics over specific periods of time.
To be able to model balking and reneging within queuing situations.
To be able to model situations involving holding and signaling entities.
To be able to model situations involving picking stations, picking up entities into groups, dropping off entities from groups, and generic station modeling.
This chapter tackles a number of miscellaneous topics that can enhance your modeling capabilities. The chapter first examines the modeling of non-stationary arrival processes. This will motivate the exploration of additional concepts in resource modeling, including how to incorporate time varying resource staffing schedules. This will enable you to better model and tabulate the effects of realistic staff changes within systems. Because non-stationary arrivals affect how statistics should be interpreted, we will also study how to collect statistics over specific periods of time.
The chapter also covers some useful modeling situation involving how entities interact within Arena. The first situation that we will see is that of reneging from a queue. This will introduce the SEARCH and REMOVE modules within Arena. Then, we will study advanced concepts involving how to signal entities based on general conditions within the system. In my opinion, this is one of the most useful modeling constructs that you will need within practice. Finally, the chapter covers some miscellaneous (but useful) topics. Specifically, as entities move through the model, they often are formed into groups. Arena’s constructs for grouping and un-grouping entities will be presented. Grouping entities is similar in some respects to batching entities, but we will see that Arena’s grouping/ungrouping functionality can lead to additional modeling flexibility. Let’s get started by looking at how time dependent arrivals can be generated.