GRG Solver Stopping Conditions

It is important to understand what the nonlinear GRG Solver can and cannot do, and what each of the possible Solver Completion Messages means for this Solver "engine." At best, the GRG Solver -- like virtually all nonlinear optimization algorithms -- can find a locally optimal solution to a reasonably well-scaled model. At times, the Solver will stop before finding a locally optimal solution, when it is making very slow progress (the objective function is changing very little from one trial solution to another) or for other reasons.

Related Topics:

Locally Versus Globally Optimal Solutions

When Solver has Converged to the Current Solution

When Solver Cannot Improve the Current Solution