Modeling and Simulation - Chapter 1

A simulation model where all variables and outcomes are predictable and have no random elements. Think of a perfectly predictable machine following set instructions.

A simulation model that includes elements of chance and randomness, like the arrival of customers at a store.

A simulation model that tracks changes over continuous periods of time, like a car's speed changing gradually.

A simulation model that tracks changes at specific discrete points in time, like the number of customers in a store at the start of each hour.

A simulation model where relationships between variables are simple and easily described with straight lines or mathematical equations.

A simulation model where relationships between variables are complex and cannot be described with simple equations. The effects of changes are not always proportional.

The first step in a simulation study, it involves clearly defining the problem and its scope.

This step involves establishing the specific aims of the simulation study and outlining the overall plan for achieving those goals.

An organized relationship of functioning units or components working together to achieve a shared goal.

A simplified representation of a real-world system used to study its behavior. It can be mathematical, computer-based, or experimental.

The process of creating a model to represent a system.

The imitation of a real-world process or system over time. It allows you to study the interactions of the parts within a complex system.

The results you get from analyzing and simulating a system. Answers questions about what the system will do and why it behaves that way.

The process of selecting the essential features of a system that are relevant to the study. It involves simplifying complex details.

A set of interrelated components acting together to achieve a common purpose.

A group of objects that are joined in some regular interaction or interdependence to accomplish some purpose.

A system where changes happen only at specific points in time, like a queuing system (e.g., bank, traffic lights).

A system where changes happen continuously over time, like the water level in a dam or a battery charging.

A system that combines both discrete and continuous dynamic behavior, like traffic on a road with traffic lights.

A system that can be measured with physical devices and has quantifiable variables (e.g., electrical, mechanical systems).

A system that relies on conceptual or imaginary measurements, often qualitative in nature (e.g., social systems, economic systems).

A system where measurements are not possible with physical tools due to its abstract nature (e.g., complex scientific models).

A system where events have absolutely no effect on each other.

A system where events affect each other in a one-way direction (A affects B, B affects C, etc.).

A system where events mutually influence each other (A affects B, and B also affects A).

Manipulating the time scale in a simulation to speed up or slow down events for better analysis.

Using simulation to understand how different factors interact and affect the performance of a system.

Exploring how changes to a system's design, layout, or transportation methods impact overall performance.

Using a simulation model to understand how a system operates, including its individual components.

Exploring hypothetical scenarios with different inputs and conditions to guide design decisions.

A system boundary defines the limits of what is included in a simulation, distinguishing it from its surroundings.

The basic components of a system, each performing a specific function, with clear input and output relations.

A change from outside a system's boundary that can affect its behavior.

An object of interest within a system. For example, a customer in a bank, a machine in a production line, or a message in a communication network.

A characteristic or property of an entity. Examples include checking account balance for a customer, speed and capacity for a machine, or length for a message.

A period of time defined by a specific length. Examples include the time required for a customer to be served, the time a machine spends welding, or the time it takes to transmit a message.

A collection of variables that describe the state of a system at any moment. They are used to track and understand system behavior.

An occurrence that happens instantaneously and can change the state of the system. Examples include the arrival of a customer, the completion of service, or the breakdown of a machine.

Describes activities and events that occur within a system. An internal process. Example: A customer completing service.

Activities and events that occur outside the system, but affect its behavior. Example: A customer arriving at the bank.

A system's classification based on its time frame. Example: Does it change rapidly over short periods or slowly over long periods?

Classifying a system based on its ability to be modeled and simulated. Examples include a system that can be replicated accurately or one with uncertainties that make prediction complex.

Classifying a system based on its interaction with its surroundings. Examples include a system that exchanges material and energy with its environment or one that is self-contained.

Important, written record of a simulation project's history, outlining work done and decisions made.

Two types: program documentation (for understanding and modifying code) and progress reports (chronological history of the project).

The success hinges on how well the previous eleven steps were executed.

An essential aspect of simulation, it helps analyze the results and determine if further runs are needed.

Involves determining the need for additional runs and designing the next set of experiments.