Controls how the genetic algorithm does crossover (also known as recombination) when two parents of the current generation reproduce to create a new child.
Crossover is one of the evolutionary biology techniques used by the genetic algorithm component, along with inheritance, mutation, and selection. In crossover, the genetic algorithm component splices out the first random n-bits of one parent and concatenates it with the last chromosome size-n bits of the other parent. The chromosome size of the child is the same as its parents.
The CrossoverMethod property controls how the break is selected: on a gene boundary, bit boundary, or byte, word, or longword boundary. Note that crossover on a non-gene boundary could possibly cause invalid gene values because the newly combined gene at the crossover point is a random mixture of bits from the 2 parents.
The Operations property controls whether crossover occurs at all during evolution, while the CrossoverProbability property controls the likelihood that crossover will occur when 2 parents are selected to create a child (e.g., if there are 100 children created each generation, the CrossoverProbability will be tested 100 times).