Define simulation; steps of simulation study

What is simulation?

Simulation is the imitation of the operation of a real-world process or system over time. We build a model of the system, run it on a computer, and observe its behaviour to draw conclusions about the real system, without building or disturbing the real one. Example: simulating customer arrivals and service at a bank counter to decide how many tellers are needed.

Steps in a simulation study

1. Problem formulation. State the problem clearly. If the client states it, the analyst checks that it is understood; if the analyst states it, the client must agree with it.
2. Setting objectives and overall project plan. Decide the questions the simulation must answer and whether simulation is the right tool. Plan the people, cost, time and the alternative systems to study.
3. Model conceptualization. Build the abstract model of the system: its entities, attributes, activities and the logic between them. Start simple and add detail only as needed. The client should take part.
4. Data collection. Collect input data (arrival times, service times, failure rates) and fit probability distributions. This runs in parallel with model building because it takes a long time.
5. Model translation. Code the model in a general language (C, Java, Python) or a simulation language/package (GPSS, Arena, Simulink).
6. Verification. Check that the program works as the conceptual model intends (debugging, tracing, step-by-step runs). "Is the model built right?"
7. Validation. Check that the model is an accurate representation of the real system by comparing its output with real data. Calibrate and repeat until accuracy is acceptable. "Is the right model built?"
8. Experimental design. Decide the alternatives to run: run length, warm-up period, number of replications, initial conditions.
9. Production runs and analysis. Run the experiments and estimate performance measures with confidence intervals.
10. More runs? Decide from the analysis whether additional runs or design changes are needed. If yes, return to step 8.
11. Documentation and reporting. Write program documentation (for future use and modification) and a progress/final report with results and recommendations.
12. Implementation. The client uses the findings. Success depends on how well the earlier steps were done and how involved the client was.

Flowchart

 Problem formulation
        |
        v
 Objectives and project plan
        |
        v
 Model conceptualization <---> Data collection
        |
        v
 Model translation
        |
        v
 Verified? --No--> (back to translation)
        | Yes
        v
 Validated? --No--> (back to conceptualization/data)
        | Yes
        v
 Experimental design
        |
        v
 Production runs and analysis
        |
        v
 More runs? --Yes--> (back to experimental design)
        | No
        v
 Documentation and reporting
        |
        v
 Implementation

Verification and validation are repeated whenever the model changes, so the process is iterative rather than strictly sequential.