Solve Advanced Settings

The required degree of precision. For a constraint to be considered satisfied, the relationship between the Cell Reference and the Constraint value cannot be violated by more than this amount.

The smaller the number, the higher the precision.

Ignore the integer, binary, and all different constraints when you run Solve.

Note: This is called solving the relaxation of the integer programming problem.

The maximum time, in seconds, that Solve runs for before it stops.

The maximum number of iterations that Solve may perform on one problem. Iterations are "pivots" for the Simplex method, or "major iterations" for the GRG method.

The limit on the number of sub-problems explored by the Branch & Bound algorithm before Solve stops.

The amount of relative change allowed in the last five iterations before Solve stops with the message Solve converged to the current solution.

Note: Providing smaller values typically means that Solve will take more time but stop at a point closer to the optimal solution.

Select the mechanism to use to estimate derivatives:

• Select Forward (default) to use forward differencing.
• Select Central to use central differencing. Central differencing yields more accurate derivatives but requires twice as many calculations of the worksheet at each new trial solution.

A number between 0 and 1 that indicates the relative frequency with which some member of the population will be altered or "mutate" to create a new trial solution during each generation or sub-problem considered by the Evolutionary method.

A higher Mutation Rate increases the diversity of the population and the chance that a new, better solution, will be found; but may also increase the total solution time.

Use the multi start method for global optimization. If this option is selected when you run Solve, the GRG Nonlinear method is run repeatedly, starting from a different (automatically chosen) starting value for the decision variable. This process may find a better solution, but will take more computing time than a single run of the GRG Nonlinear method.

The number of different starting points (values for the decision variables) for the method to consider:

• The minimum population size is 10.
• If you supply a value that is less than 10, or leave the field empty, it is automatically set to 10 times the number of decision variables up to a maximum population size of 200.

The random seed for the random number generator used when creating candidate starting points for your selected method. The seed number entered here is used as a fixed starting point for the random number generator:

• If you enter a number, that number is used as the starting point by the random seed generator each time you run Solve.
• If you do not enter a number, the random number generator uses a different seed each time you run Solve. This may yield a different (better or worse) solution each time.

The maximum number of seconds you want the Evolutionary method to continue for without a meaningful improvement in the objective value of the best solution in the population. After this time, Solve will stop with the message Solve cannot improve the current solution.