Simulation & Modeling: Steps of Modeling Process Part 2

Study Notes

Model Implementation involves translating the conceptual design into a functioning simulation program.
Tools like SIMAN or GPSS are commonly used; programming languages such as C++ and Java can also be utilized.
Non-programmers can run simulations and analyze results through graphical environments.
Appropriate hardware configurations are necessary for effective model execution.

Verification checks if the model solves the problem correctly, while validation ensures it addresses the right problem.
Solutions need to account for long-term effectiveness, not just short-term feasibility.
Robust models can predict performance across various input scenarios and should be compared against historical data.
If weaknesses are found, revisit earlier steps to simplify or refine the model.

Models can operate in two states: Terminating (runs for a set time) and Steady State (continuous operation).
Initial conditions significantly influence outcomes and must be clearly defined for simulations.
For terminating systems, run simulations from start to finish multiple times for diverse conditions.
In steady-state conditions, sample data at various intervals during each run for accuracy.

Statistical methods are used to analyze outputs, determining how closely they align with real-world systems.
The analysis methodology differs based on whether the system is terminating or steady-state.
For steady-state models, data should be assessed after achieving statistical equilibrium to avoid initial condition bias.

Reports should articulate the model’s purpose, findings, and can be shared among researchers and engineers.
Analysis of the Problem section outlines goals clearly.
Model Design must detail data, relationships, and visual aids like graphs and diagrams.
In Model Solution, describe problem-solving techniques with user-friendly equations and clear information.
Results and Conclusions should present findings, interpretations, implications, and recommendations for future work.

Changes to real systems based on model results should be cost-effective, considering potential savings or revenue increases.
Evaluate the impact of proposed changes on interconnected systems.
Models can provide crucial insights when suggesting modifications to existing systems.

The simulation initiates with the main program invoking the initialization routine, starting with the timer set to zero.
Initialization includes setting the system state, statistical counters, and event lists.
The main program manages when to call the timing routine to assess upcoming events.
When an event is due, the simulation clock updates to reflect its time, prompting the main program to invoke the event routine to update system states and counters.