Home → Techniques and Tips → Evolver and RISKOptimizer → Running RISKOptimizer Deterministically
I would like to use RISKOptimizer's optimization, but without running Monte Carlo simulations. How can I run RISKOptimizer deterministically rather than stochastically?
We recommend using Evolver rather than RISKOptimizer for deterministic optimization, for these reasons:
Evolver is part of the DecisionTools Suite and is also available as a separate product. If you don't have access to Evolver, ...
While RISKOptimizer usually runs a simulation optimization, you can also run it deterministically. For an overview, please refer to the diagram in the user manual, in the section "Traditional Optimization vs. Simulation Optimization".
In RISKOptimizer, there are actually two types of variables:
If you don't have any PDFs, you have a deterministic model. You still have the adjustable cells, and RISKOptimizer will try different values of them in each simulation. Since there are no PDFs, every iteration within a given simulation would produce the same result. Therefore, you want to set one iteration per simulation, and optimize for value.
To run RISKOptimizer deterministically:
In 6.x/7.x, on the toolbar or ribbon, set Iterations to 1. Also, in the Model Definition, set Optimize to Value.
Note: The linear programming features included in Evolver 6.x/7.x are not available in RISKOptimizer. If you have a deterministic LP problem, we recommend using Evolver to solve it.
In 5.x, open Optimization Settings and go to the Runtime tab. Near the bottom, under "Simulation Runtime", click the radio button next to Iterations and set the iteration count to 1.
In 1.x, open RISKOptimizer Settings and click Options. Near the bottom, under Simulation Stopping Conditions, select Run and 1 iteration.
If your RISKOptimizer model contains @RISK probability distribution functions, you can lock them to their static values during the optimization, if you wish. See Turning Inputs On and Off.
Last edited: 2018-04-02