Home → Techniques and Tips → Evolver and RISKOptimizer → Starting Values of Adjustable Cells
Applies to:
Evolver 1.x–7.x
RISKOptimizer 1.x
@RISK Industrial 5.x–7.x (RISKOptimizer)
Does it matter what values are in the adjustable cells when I click the start button for an optimization?
With the genetic algorithm, it matters very much. With the OptQuest engine, it matters very little.
The OptQuest engine was added in Evolver 6.0 and @RISK Industrial 6.0's Optimizer. With those and later versions, you can select the engine on the Engine screen of the Settings dialog. If you leave the default setting of Automatic, the software will select the engine that seems more appropriate.
With OptQuest, the starting solution is really just a suggested solution, and the algorithm includes a method for generating feasible solutions (all constraints met) even if the initial values don't meet constraints.
The genetic algorithm, which was the only algorithm in earlier releases and is still an option in 6.x, includes backtracking as an important strategy. When Evolver or RISKOptimizer strikes out from where it was standing and that doesn't make the target cell get closer to the goal, then the optimizer backtracks to its previous position and strikes out in a new direction. This has two consequences for the genetic algorithm:
It's extremely important to have an initial feasible solution (all constraints met) before you click the start button. If the initial values of the adjustable cells don't represent a feasible solution, the optimizer may have to strike out in many directions to find a feasible solution before it can then really begin the main optimization. For more on this, and help in finding an initial feasible solution, please see Debugging RISKOptimizer and Evolver Models.
Perhaps your problem has one or more local optimum points as well as a global optimum. If the initial values in the adjustable cells are close to a local optimum, Evolver or RISKOptimizer may home in on the local optimum instead of the global optimum. If this happens, starting from a very different set of values (though still meeting all constraints) may let the optimizer find a better solution.
Last edited: 2015-07-23