TABLE OF CONTENTS Simulation modeling is a common paradigm for analyzing complex systems. In a nutshell, this paradigm creates a simplified representation of a system under study. The paradigm then proceeds to experiment with the system, guided by a prescribed set of goals, such as improved system design, cost benefit analysis, sensitivity to design parameters, and so on. Experimentation consists of generating system histories and observing system behavior over time, as well as its statistics. Thus, the representation created (see Section 1.1) describes system structure, while the histories generated describe system behavior (see Section 1.5).
This book is concerned with simulation modeling of industrial systems. Included are manufacturing systems (e.g., production lines, inventory systems, job shops, etc.), supply chains, computer and communications systems (e.g., client-server systems, communications networks, etc.), and transportation systems (e.g., seaports, airports, etc.). The book addresses both theoretical topics and practical ones related to simulation modeling. Throughout the book, the Arena/SIMAN (see Kelton et al. 2000) simulation tool will be surveyed and used in hands-on examples of simulation modeling.
This chapter overviews the elements of simulation modeling and introduces basic concepts germane to such modeling.
Modeling is the enterprise of devising a simplified representation of a complex system with the goal of providing predictions of the system's performance measures (metrics) of interest. Such a simplified representation is called a model. A model is designed to capture certain behavioral aspects of the modeled system those that are of interest to the analyst/modeler in order...
