2. Introduction
• Simulation system design is a
systematic approach to creating
computer-based models that
simulate the behavior of real-world
systems. It allows us to study
complex systems, make informed
decisions, and optimize system
performance. The principles of
simulation system design provide a
framework for effectively designing
and developing simulation systems.
3. Principle 1: Problem
Definition
• The first principle of simulation system
design is problem definition. It
involves clearly understanding the
problem that the simulation system
aims to address. This includes
identifying the objectives, scope, and
constraints of the simulation. Proper
problem definition ensures that the
simulation system focuses on the right
aspects and provides meaningful
insights and solutions.
4. Principle 2:
Model
Development
• The second principle is model
development. It involves creating
a mathematical representation of
the system being simulated. This
includes identifying system
components, their relationships,
and the rules that govern their
behavior. The model should
accurately capture the system
dynamics and interactions to
provide reliable simulation
results.
5. Principle 3: Data
Collection and
Validation
• The third principle is data collection
and validation. It involves collecting
relevant data from the real-world
system to ensure the accuracy of the
simulation model. This includes data
on system behavior, performance, and
constraints. Validation involves
comparing the model outputs with
observed data to ensure that the
simulation reflects the real-world
system accurately.
6. Principle 4: Verification
and Validation
• The fourth principle is verification and
validation. Verification ensures the
correctness of the simulation model
implementation. It involves checking
the model's equations, algorithms,
and logical structure. Validation, on
the other hand, involves comparing
the model outputs with observed data
and conducting sensitivity analyses to
ensure the model's accuracy and
reliability.
7. Principle 5: Experimentation
and Analysis
• The fifth principle is experimentation
and analysis. It involves conducting
simulation experiments to gain
insights into the system's behavior. By
running multiple scenarios and
analyzing the results, we can evaluate
different strategies, optimize system
performance, and identify
improvement opportunities.
Experimentation and analysis help
decision-makers make informed
choices based on evidence and data.
9. Simulation
System and
Language:
• A simulation system comprises various
components, including the simulation
language. The simulation language
provides a set of rules and syntax for
defining and executing simulation
models. It allows users to specify
system components, events, and
behaviors. Different simulation
languages are available, each with its
own features and capabilities to cater
to different modeling requirements.
11. Conclusion:
• Simulation system design is a
powerful tool for understanding and
analyzing complex systems. By
following the principles of
simulation system design and
utilizing appropriate simulation
languages, we can gain valuable
insights, optimize system
performance, and make informed
decisions that drive success. Proper
problem definition, accurate model
development, data validation,
verification, experimentation, and
analysis are key elements for
building effective simulation
systems.
