Organization of the Book
Chapter 1 is an introduction to the field of simulation modeling. After Chapter 1 the student should know what simulation is and be able to put the different types of simulation into context. Chapter 2 introduces the basics of Monte Carlso simulation and discrete event systems. It also emphasizes the important concept of how a discrete-event clock “ticks” and sets the stage for process modeling using activity diagramming. Finally, a simple (but comprehensive) example of Arena is presented so that students will feel comfortable with the tool.
Chapter 3 reviews issues in statistical concepts for the case of finite horizon simulation studies. This chapter should provide a refresher for students on statistical concepts. Chapter 4 dives deeper into process-oriented modeling. The Basic Process template within Arena is thoroughly covered. Important concepts within process-oriented modeling (e.g. entities, attributes, activities, state variables, etc.) are emphasized within the context of a number of examples. In addition, a deeper understanding of Arena is developed including flow of control, input/output, variables, arrays, and debugging. After finishing Chapter 4, student should be able to model interesting systems from a process viewpoint using Arena. Chapter 5 returns to statistical issues within the context of infinite horizon simulation. In addition, the concepts of verification and validation are discussed.
Chapters 6 and 7 present more advanced concepts within simulation and especially how Arena facilitates the modeling. In particular, non-stationary arrivals and resource staffing are introduced in Chapter 6, as well as constructs for generic station modeling, picking up and dropping off entities. Chapter 7 presents a thorough treatment of the entity transfer and material handling constructs within Arena. Students learn the fundamentals of resource-constrained transfers, free path transporters, conveyors, and fixed path transporters. The animation of models containing these elements is also emphasized.
Finally, Chapter 8 presents a detailed case study using Arena. An IIE/Rockwell Software Arena Contest problem is solved in its entirety. This chapter ensures that students will be ready to solve such a problem if assigned as a project for the course. The chapter wraps up with some practical advice for performing simulation projects.
Adopters of previous editions of this textbook will notice that the topics of random number generation, random variate generation, input distribution modeling, and queueing theory have been moved to the appendix. The material in those chapters is presented in a manner that is as independent as possible from the tool of Arena. This allows instructors to form a natural progression on Arena (through chapters 1-8), but also have the flexibility to cover random number generation, random variate generation and input distribution modeling if those topics are not covered in another course.