This option is normally set to Standard. It uses internally the standard parameters of the genetic algorithms with population= 20, crossover = 0.8 and mutation =0.02. Set the option to Manual to edit these parameters.
Population Size
A population represents a set of the optimization variables as nominal and stochastic design parameters (individuals). The population size is the number of the sets of design parameters at each optimization step a a generation. It characterizes the number of simulation runs in an optimization step. For each set of optimization variables, a simulation run must be executed.
Crossover Rate [0..1]
It is a probability to crossover (recombination) for 2 individuals selected from the population. Thre is no individual being crossover at 0 and all individuals of the population will be pairwise recombinate at 1.
Mutation Rate [0..1]
It is a probability to mutate for an individual selectd from the population. Thre is no mutation at 0 and all bits of the individual will be mutated at 1.
Selection
It is a kind how to select the individuals from the population to generate new population. There are 4 types: "Roullet Wheel", "Rank", "Tournament" and "Stochastic Universal Sampling"
Crossover
This is a kind how to recombine 2 individuals selected from the population to generate new population. There are 3 types: "One-Point", "Two-Point" and "Uniform"
Hypervolume computing
The option turns on or off the computing of hypervolume for multi-objective optimizazion.