How do you optimize your simulation parameters and scenarios for different objectives and constraints?

1 Define your objectives

The first step is to define what you want to achieve with your simulation. What are the key performance indicators (KPIs) that you want to improve or optimize? For example, you might want to reduce the cycle time, increase the throughput, minimize the waste, or maximize the profit. You also need to specify the target values or ranges for your KPIs, and the priority or weight of each objective.

2 Identify your constraints

The second step is to identify the constraints or limitations that affect your simulation. Constraints are the factors that you cannot change or control, but that have an influence on your objectives. For example, you might have a fixed budget, a limited space, a certain demand, or a specific quality standard. You need to define the values or boundaries for your constraints, and the penalty or cost of violating them.

3 Choose your simulation parameters

The third step is to choose the simulation parameters that you can vary or manipulate to achieve your objectives. Parameters are the factors that you can change or control, and that have an impact on your KPIs and constraints. For example, you might have different machine settings, operator schedules, inventory levels, or process flows. You need to determine the possible values or options for each parameter, and the range or interval of variation.

4 Generate your simulation scenarios

The fourth step is to generate the simulation scenarios that you want to compare and evaluate. A scenario is a combination of values or options for your parameters, constraints, and objectives. You can generate scenarios manually, by selecting or assigning values to each parameter, or automatically, by using a random or systematic method. You need to ensure that your scenarios are feasible, realistic, and representative of your production system.

5 Run your simulation experiments

The fifth step is to run your simulation experiments and collect the results. An experiment is a simulation run with a specific scenario and a predefined duration or number of repetitions. You can run experiments individually, by executing each scenario separately, or in batches, by running multiple scenarios simultaneously or sequentially. You need to use a reliable and accurate simulation software, and a sufficient sample size or confidence level.

6 Analyze your simulation outputs

The sixth step is to analyze your simulation outputs and select the best scenario or solution. An output is a measure or value of your KPIs, constraints, or objectives for each experiment or scenario. You can analyze outputs visually, by using graphs, charts, or tables, or statistically, by using methods such as optimization, sensitivity analysis, or trade-off analysis. You need to compare and rank your outputs according to your criteria and preferences.