Discrete-event simulation: The system is modelled as it develops through time with the help of a representation in which the state of the system changes at distinct moments in time. These changes occur with the help of events. Event: occurrence at which the state of the system immediately changes. For example, a machine starts processing a product (state of machine changes from available to occupied).
Event-oriented: simulation model is created by modelling all events that might occur. Thus, modelling of the arrival of an entity, start of processing an entity and leaving of an entity.
Process-oriented: simulation model is created by using the way of the entity going through the system. Thus, modelling of all processes, such as machines, vehicles, related to entities. Arena: One of the many available software packages that you can use to build a simulation model. Arena uses process-oriented modelling. The actual realisation (running of your model) is event-oriented. Performance measures: goal of your study. Decide on which performance measures you want to collect data. Examples of performance measures are waiting times, average number of products in system and throughput times.
Parts of a simulation model Entity: dynamic objects that move around in your model and that can change the status of other objects in the model. Entities are created when they arrive in the model, move around in the model, are served and leave the model. Different types of entities might be present in your model. First of all, we create real things, such as products or persons that make use of processes in the system.
The Term Paper on Our Tax System Needs Changing
Our current tax system is complex, costly, and unfair. Surely, America can do better for our children than redistribution and regulation. Our nation is over four trillion dollars in debt. It is time to act instead of letting lawyers and politicians play with our money. A flat tax plan is a simple solution to remedy the stagnant apathy our nation has been so accustomed to for the last seventy ...
Secondly, we can create virtual entities that can be used to change the status of your system (e. g. a shop that is open or closed) or the status of a machine (e. g. the machine is available or broken down).
Resources: objects that perform service on entities. Entities will compete for the service of a resource. Entities will claim, use and release a resource while they are in the system. Examples of resources are: machines, employees, tables in a restaurant, available space in the storage area of a warehouse and so on. Resources can have a capacity of one or higher.
This capacity might change during your simulation study. Queue: waiting area for an entity that is waiting to continue its way in the system. A queue is usually related to a resource and offers an entity the opportunity to wait for a resource being available to provide service (e. g. waiting line for check-in counter at an airport).
Queues either have a finite or infinite capacity. Characteristics of queues are important performance measures of a system. Simulation clock: The clock of Arena is event-driven. Thus, if you are running your model, the time between two successive events will be skipped.
Statistical accumulators: used to keep track of values of defined performance measures. You can define them by yourself. Attribute: characteristic of entities. The specific value of an attribute will vary per entity and can be used to describe or distinguish between entities. Keep in mind that this value is tied to a specific entity and can only be derived from this entity. Examples of attributes include: the colour of a car, the arrival time in the system and the processing time at a machine. Variable: information accessible to the entire model. Each variable is unique.
