Chapter 2 Introduction to Simulation and Arena


  • To understand the basic components of the Arena Environment

  • To be able to perform simple Monte Carlo simulations in Arena

  • To be able to recognize and define the characteristics of a discrete-event dynamic system (DEDS)

  • To be able to explain how time evolves in a DEDS

  • To be able to develop and read an activity flow diagram

  • To be able to create, run, animate, and examine the results of an model of a simple DEDS

In this chapter, we explore the Arena simulation software platform for developing and executing simulation models. After highlighting the Arena modeling environment, we will consider some small models for both static and dynamic simulation. The coverage of static simulation will allow us to introduce the modeling environment without having to introduce the notion of the discrete-event clock. Then, we will begin our study of the major emphasis of this textbook: modeling discrete-event dynamic systems. As defined in Chapter 1, a discrete-event dynamic system (DEDS) is a system that evolves dynamically through time. This chapter will introduce how time evolves for DEDSs and illustrate how to develop a model for a simple queuing system. Let’s jump into Arena.