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# Select '''Ascending''' or '''Descending''' option to sort the output in ascending or descending order, respectively.
# Click '''OK''' to run the optimization and generate the Optimization Report.
<br>
== Running Genetic Algorithm Search ==
<div style="background-color: #E3FBE5;">Note: For detailed information on Genetic Algorithm properties, see [[Understanding Optimization#Understanding Genetic Algorithm Optimization]]</div>
Optimization is performed from the '''Format Objects''' window:
To perform Genetic Algorithm optimization:
# Open the '''Format Objects''' window.<br><span>{{FormatObjectIS}}</span>
# Select the '''Signals''' tab.
# Click the '''Optimize''' button.
# In the '''Select Optimization Method''' dialog box that appears, select '''Genetic Algorithm'''.
# In the '''Genetic Algorithm Properties''' window that opens, select the '''Optimizable Inputs''' tab.
# In the '''Start Value''' column, enter the desired starting values for each of the inputs.
# In the '''End Value''' column, enter the desired ending values for each of the inputs.
# In the '''Step''' column, enter the desired step size, for each of the inputs.
# Select the '''Algorithm-specific Properties''' tab.
# Select criteria:
#: 1. Select '''Standard Criteria'''.
#: 2. Select the criteria from the drop-down list. [[Performing_Optimization#Standard Criteria|Read more about Standard Criteria]].<br>or:<br>
#: 1. Select '''Custom Criteria'''.
#: 2. Click '''Edit...''' button.
#: 3. Write the script for the custom criteria. [[Performing_Optimization#Custom Criteria|Read more about Custom Criteria]].
#: 4. Click '''OK'''.
# Select '''Ascending''' or '''Descending''' option to sort the output in ascending or descending order, respectively.
# An optimum population size value is automatically placed into the '''Population Size''' box; if a different value is desired, enter the value into the box.
# In the '''Crossover Probability''' box, enter the desired crossover probability; value range is 0.95-0.99, with a default of 0.95.
# In the '''Mutation Probability''' box, enter the desired mutation probability; value range is 0.01-0.05, with a default of 0.05.
# In the '''Convergence Type''' drop-down list, select '''Number of Generations''' or '''Proximal Convergence'''.
# In the '''Maximum Number of Generations''' box, enter the desired maximum number of generations.
# If Proximal Convergence was selected, enter the desired minimum number of generations and convergence rate into the respective boxes. A value, approaching 1 is usually selected for the convergence rate; the default value is 0.990000.
# In the '''Genetic Algorithm Subtype''' drop-down list, select '''Basic''' or '''Incremental''' algorithm subtype.
# If Basic algorithm subtype was selected, select '''Yes''' or '''No''' for '''Use Elitism''' option.
# If Incremental algorithm subtype was selected, select the '''Replacement Scheme''' and '''Offspring Number''' (number of “children”).
# Click '''OK''' to run the optimization and generate the Optimization Report.<br>
[[Category:Optimization]]
