Simulations Ideology

A simulation—as defined by Jerry Banks et al. in their book Discrete-Event System Simulation—is an “imitation of the operation of a real-world process or system over time.”[1] Since the advent of digital computation and computer simulations, their utility have become much greater, and are now utilized within a wide range of applications, including various types of manufacturing, construction engineering, military, logistics, transportation, distribution, business processes, and human systems.[2] Because of this array of uses, it is important to first determine the type of system that the simulation is required to imitate. The system—as defined by Banks et al.—is “a group of objects that are joined together in some regular interaction or interdependence toward the accomplishment of some purpose.”[3] He states, “In order to understand and analyze a system, a number of terms need to be defined. An entity is an object of interest in the system. An attribute is a property of an entity. An activity represents a time period of specified length. If a bank is being studied, customers might be one of the entities, the balance in their checking accounts might be an attribute, and making deposits might be an activity.”[4]

Learning from this, it is then possible to investigate various other systems. Within a pool of water, the entities would be the water particles, with their location, velocity, and mass being some of the possible attributes, and colliding with each other being one of the possible activities. (Fig. 2.1.1) The same can be observed in a traffic system, where the cars would be the entities, with their location, size, color, and car typology being possible attributes, and starting or stopping being possible activities. (Fig. 2.1.2) Taking this investigation then, to a crowd of people, it can be abstracted that the individual people would be the entities, with their location, gender, height, weight, etc. being possible attributes, and their various interactions with one another being activities. (Fig. 2.1.3)

Of course, these are just generic assumptions, since “a complete list cannot be developed unless the purpose of the study is known.”[5] However, by investigating these assumed systems, a pattern can be noticed. From the water example, each particle interacts with surrounding particles through collision, which are affected by the particle attributes such as velocity and mass. If one were to toss a rock into the water, the rock would offset local particles at the point of impact, which will interact with particles around it, producing ripple waves within the system. From the traffic example, it can be observed that when one car slows down the subsequent car slows down as well, producing an offset until there is a wave of phantom traffic within the road. From the crowd example, it can then be observed that the people, much like the water particles, collide into one another, each instigating interaction locally as they ripple throughout the space, once again producing a wave-like pattern.