Use Automatic Scaling

When this box is checked, the Solver will attempt to scale the values of the objective and constraint functions internally in order to minimize the effects of a poorly scaled model. A poorly scaled model is one in which the typical values of the objective and constraint functions differ by several orders of magnitude. A classic example is a financial model with some dollar amounts in millions, and other rate of return figures in percent. Poorly scaled models may cause difficulty in the solution process, again due to the effects of finite precision computer arithmetic.

Poorly scaled models are one of the most common causes of problems in which the Solver appears to stop prematurely without reaching the true optimal solution; it is a good idea to keep this box checked for all of your Solver models.

If your model is nonlinear and you do check the Use Automatic Scaling box, make sure that the initial values for the decision variables are "reasonable," i.e. of roughly the same magnitudes that you expect for those variables at the optimal solution. The effectiveness of the Automatic Scaling option depends on how well these starting values reflect the values encountered during the solution process.