Specify moga optimization function options.


options = mogaoptimset('option1', value1, 'option2', value2, ...)


The name of option N.
The value of option N.


A struct containing the options.
The available options are as follows:
  • MaxIter: The maximum number of iterations allowed.
  • MaxFail: The maximum number of failed sample evaluations.
  • PopulationSize: The number of initial sample points.
  • TolCon: The constraint violation allowance, as a percent.
  • CrowdDist: The space in which the crowding distance is evaluated. Choose 0 for the design space, 1 for the solution space, and 2 for both.
  • Seed: The seed for the random number generator.
  • Display: An 'iter'/'off' flag to indicate whether objective function results will be displayed at each iteration. For more extensive iteration information see the output return argument of the optimization function.


Set options to control the number of iterations and display intermediate data:

options = mogaoptimset('MaxIter', 200, 'Display', 'iter')

options = struct [
Display: iter
MaxIter: 200


The default value for MaxIter is 50. The mininum value is 25.

The default value for MaxFail is 20000.

The default value for PopulationSize is 0, which allows the algorithm to choose.

The default value for TolCon is 0.5 (%).

The default value for CrowdDist is 0.

The default value for TolCon is 0.5. It only applies when moga cannot find a feasible solution. In such cases the function will return the best infeasible solution found within the allowed violation, along with a warning. The algorithm does not attempt to minimize the utilized violation. The TolCon value is applied as a percent of the constraint bound, with an absolute minimum of 1.0e-4 applied when the bound is zero or near zero.

The default value for Seed is 0 (unrepeatable).

The default value for Display is 'off'.