OR 508

Simulation is defined as: Solving mathematical equations. Imitation of a real-world system over time. Direct experimentation. Optimization of systems.

Simulation involves: Real history observation. Artificial history generation. Field experiments. Analytical proofs.

A simulation model is mainly used to: Replace the real system. Solve deterministic problems. Eliminate uncertainty. Study system behavior over time.

A model is best described as: A computer code. A physical prototype. A conceptual framework describing a system. A database.

Simulation models are based on: Assumptions. Exact solutions. Physical laws only. Trial and error.

One main goal of simulation is to: Reduce variables. Answer “what-if” questions. Eliminate randomness. Optimize mathematically.

Simulation is useful for: Predicting system impact of changes. Eliminating system errors. Replacing experiments. Avoiding modeling.

Simulation is better performed: After implementation. During maintenance. Before implementation. During failure.

Simulation can be used as: A training tool. A replacement for theory. A repair method. A data collection tool only.

Simulation helps to: Increase uncertainty. Identify adequate parameters. Eliminate assumptions. Avoid modeling.

Mathematical methods are: Suitable for complex systems. Accurate with few parameters. Easy to apply to all systems. Based on simulation.

Mathematical methods become impractical when systems are: Small. Linear. Complex. Deterministic.

Numerical computer-based simulation is: Difficult. Limited. Useful for complex systems. Only theoretical.

Numerical simulation is preferred because it is: Simple and flexible. Exact. Analytical. Deterministic.

Simulation is mainly used when: Analytical solution is easy. System is very simple. System is complex. No randomness exists.

Simulation is appropriate to study: External factors only. Internal interactions. Single-variable systems. Static systems.

Simulation allows testing: Only existing systems. Manual procedures. Past systems. New designs and policies.

Simulation can be used for: Machine requirement determination. Exact optimization. Removing queues. Eliminating delays.

Animated simulation helps in: Coding. Visualization. Debugging hardware. Eliminating randomness.

Modern systems often require simulation because they are: Simple. Small. Too complex. Deterministic.

Simulation is not suitable when: Problem is complex. Analytical solution exists. System is large. Time is available.

Simulation should be avoided if: Cost exceeds savings. System is stochastic. Time is compressed. Output is graphical.

Simulation is not recommended when: Direct experiments are easier. System is complex. There is randomness. Data is available.

Human behavior is difficult to simulate because it is: Simple. Linear. Too complex. Deterministic.

Simulation is unnecessary when: Common sense solves the problem. System is dynamic. System is stochastic. System is discrete.

Simulation models are: Solved. Run. Optimized. Linearized.

Simulation allows experimentation without: Time. Cost. Disrupting real systems. Data.

Simulation helps test: Software only. New hardware designs. Theoretical models only. Simple systems only.

Simulation can compress or expand: Time. Cost. Resources. Events.

Bottleneck analysis is possible through: Optimization. Simulation. Experimentation. Observation.

Simulation modeling requires: No training. Hardware only. No expertise. Special training.

Simulation results can be: Always clear. Difficult to interpret. Exact. Unique.

Simulation studies are often: Cheap. Quick. Time-consuming. Instant.

Simulation software often includes: No analysis tools. Output-analysis tools. Only templates. No visualization.

Simulation vendors provide: Templates. Hardware. Analytical solutions. Experiments.

Simulation is widely used in: Manufacturing. Literature. Philosophy. Art.

Semiconductor manufacturing uses simulation to: Eliminate randomness. Model complex processes. Replace machines. Reduce theory.

Simulation is applied in: Healthcare. Logistics. Transportation. All of the above.

Network simulation includes: CPU only. Memory only. LAN and wireless. Storage only.

Simulation is used in risk analysis for: Insurance. Portfolios. Both A and B. None.

A system is: A random collection of objects. Objects interacting for a purpose. Independent elements. Static components.

A factory is an example of: Open system. Closed system. Isolated system. Random system.

System environment refers to: Internal variables. External influences. System objectives. Model structure.

Customer arrivals in a bank are: Internal activities. Environmental effects. State variables. Attributes.

System output may affect: System environment. Model size. Random numbers. Time scale.

An entity is: A property. An object of interest. A time period. A state.

Attribute refers to: Object behavior. Entity property. Event. Activity.

An activity represents: Instant change. A time duration. A random event. A state variable.

An event is: Continuous change. Long activity. Instantaneous occurrence. Attribute.