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2.3. Iterations versus Simulations versus Trials

Applies to:
@RISK 6.x/7.x ("Trials" applies to @RISK Industrial)

What's the difference between iterations and simulations in Simulation Settings? Which one should I set to which number?

An iteration is a smaller unit within a simulation. At each iteration, @RISK draws a new set of random numbers for the @RISK distribution functions in your model, recalculates all open workbooks or projects, and stores the values of all designated outputs. At the end of a simulation, @RISK prepares any reports you have specified.

For example, if you run 5000 iterations and 3 simulations, then at the end of the analysis you can look at three histograms for each @RISK output. Each histogram summarizes the 5000 values for the 5000 iterations of one of the three simulations.

You can set the numbers of iterations and simulations in the @RISK ribbon, or on the General tab of Simulation Settings. For most analyses, you will want N iterations and 1 simulation. If you use the same set of assumptions for all simulations, you will usually get better results with one simulation of 15000 iterations than with three simulations of 5000 iterations.

But setting simulations greater than 1 is useful in several situations, such as these examples:

Suppose one or more unknown quantities are under your control, such as several different prices you might charge or several different raw materials you might use. You would like to know what the different choices would do to your bottom line. In this case the different values of the unknown quantity(ies) would be in one or more RiskSimtable functions. See the topic "Sensitivity Simulation" in your @RISK manual or @RISK help.
In a similar way, if you have several assumptions or scenarios you can embed them in one or more RiskSimtable functions and run one simulation on each, all as part of one analysis.
To test the stability of your model, you might run several simulations with the same model and without RiskSimtable functions. If the simulation results are fairly close, you know that your model is stable; if they vary significantly, you know that your model is unstable or you are not running enough iterations. For simulation settings to set the random number seed, see "Multiple @RISK Simulation Runs" in Random Number Generation, Seed Values, and Reproducibility.

I'm running an optimization with RISKOptimizer. How to trials relate to simulations or iterations? Why is the number of valid trials different from the number of trials?

RISKOptimizer places a set of values in the adjustable cells that you designated in the Model Definition, then runs a simulation. At the end of the simulation, RISKOptimizer looks at the result and decides whether enough progress has been made o declare the optimization finished. That is one trial. On the next trial, RISKOptimizer places a different set of values in the adjustable cells—using the results of earlier trials to decide which values—and then runs another simulation.

The difference between trials and valid trials depends on your hard constraints. A valid trial is one that meets all hard constraints. If a trial is not a valid trial, RISKOptimizer throws away the result of that simulation. If your proportion of valid trials to total trials is small, you may want to look at restructuring your model so that the optimization can make progress faster. For more, see For Faster Optimizations.

Additional keywords: Simtable

Last edited: 2018-06-11

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