How can you simulate different scenarios in operations research?

1 Define the problem and objectives

The first step in any OR project is to define the problem and objectives clearly. What are you trying to achieve? What are the main variables and constraints? What are the relevant criteria and measures of success? You should also identify the scope and boundaries of the system you want to model, and the level of detail and accuracy you need. A well-defined problem and objectives will guide the rest of the simulation process and help you focus on the most important aspects.

2 Build the model

The next step is to build a mathematical or logical representation of the system you want to simulate. This can be done using various methods, such as flowcharts, equations, diagrams, or computer programs. The model should capture the essential features and behaviors of the system, such as its inputs, outputs, processes, resources, and interactions. You should also define the parameters and variables that can be changed or controlled in the simulation, such as demand, capacity, costs, or policies. The model should be as simple as possible, but as complex as necessary, to meet your objectives.

3 Collect and analyze data

To make your model realistic and reliable, you need to collect and analyze data from the real system or from similar sources. Data can include historical records, observations, surveys, experiments, or expert opinions. You should use statistical methods to summarize, organize, and validate the data, and to estimate the distributions and relationships of the variables. Data analysis will help you calibrate and verify your model, and to identify the sources and levels of uncertainty and variability in the system.

4 Run the simulation

Once you have a valid and tested model, you can run the simulation under different scenarios. A scenario is a set of assumptions or conditions that affect the behavior and performance of the system. For example, you can simulate how the system will respond to changes in demand, supply, prices, regulations, or technology. You can also simulate how different policies or strategies will affect the system's outcomes and objectives. To run the simulation, you need to specify the initial values and settings of the model, the duration and frequency of the simulation, and the outputs and indicators you want to measure and record.

5 Analyze the results

The final step is to analyze the results of the simulation and draw conclusions and recommendations. You should use graphical and numerical methods to summarize, compare, and evaluate the results of different scenarios. You should also perform sensitivity analysis to determine how the results change with different values of the parameters or variables. You should interpret the results in relation to your objectives and criteria, and identify the best or most optimal scenario for your decision making. You should also report the limitations and assumptions of your model and simulation, and the sources of uncertainty and error.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?