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# After a number of all possible combinations is determined, an optimal number of individuals is selected.
# Each individual is selected at random. These individuals form the first Generation. The optimal number of individuals is automatically placed in next to the '''Set Population Size''' field box and can be changed manually.<br><div style="background-color: #E5F6FF;">Tip: An excessively large Population Size value will result in an increase in calculation time, while an overly small Population Size value will result in a decrease in calculation accuracy.</div><br><div style="background-color: #E3FBE5;">Note: MultiCharts' GA support artificially exclusive population. This means that identical individuals cannot exist inside the same population, and thus the population size can not exceed the total number of input combinations. The population size is constant for each generation.</div>
# The fitness of each individual is evaluated and the least fit individuals discarded.
# A new population of individuals is generated from the remaining members of the previous population by applying the crossover and mutation operations, as well as selection and/or replacement strategies that depend on the GA subtype: <br>
#: '''GA Subtypes and Replacement Schemas'''
#: GA subtype defines the way that GA creates new individuals and replaces old individuals when creating next generations.
#: GA subtype can be set in the '''Genetic Algorithm Subtype''' drop-down listsection.
#: Two GA subtypes are available: '''Basic''' and '''Incremental'''.
#: '''Basic''' subtype is the standard so-called “simple genetic algorithm”. This algorithm uses non-overlapping generations and Elitism mode (optional). For each generation, the algorithm creates an entirely new population of individuals (if the '''Elitism''' option is selected, the most fit individuals move on to the next generation).<br>
#: '''Worst''' – least fit individuals are replaced
#: '''Parent''' – parent individuals are replaced
#: '''Random''' – individuals are replaced randomly<br>#: '''Offspring Number''' #: Offspring Number is the number of children to be added each time that a new generation is created. '''One''' or '''Two''' children can be added.
# The fitness of each individual is evaluated and the least fit individuals discarded.
# The process is repeated, until the specified degree of convergence or generation number is reached (depends on GA setting selected).<br>
#: '''Terminate-Upon-Generation''' will stop the optimization process once the specified '''Maximum Number of Generations''' is reached.
#: '''Terminate-Upon-Convergence''' will stop the optimization process once the defined '''Convergence Rate''' is reached, or once the defined '''Maximum Number of Generations''' is reached.<br>
#: GA optimization "ending-point" criterion is selected in the '''Conversion Type''' drop-down listsection.
#: The desired Maximum Number of Generations, Minimum Number of Generations, and Conversion Rate can be set in the corresponding text boxes.<br>
#: '''Convergence Rate'''
