Machine learning enables computers to mimic human behaviour by teaching them historical data and knowledge about possible future events. This section will examine fascinating machine learning methods such as Crossover, edge recombination operator, and fly algorithm. Crossover Crossover, also known as recombination, is a genetic operator used in genetic algorithms and evolutionary computation to merge the genetic information of two parents to produce new offspring.

It is comparable to the crossover during sexual reproduction in biology and represents one approach to stochastically making new solutions from an existing population. Cloning a current solution, which is comparable to asexual reproduction, is another way to create new solutions. Usually, new solutions are mutated before being introduced to the population. Moreover, each genetic representation can be paired with various crossover operators, and various evolutionary computation methods may employ different data structures to store genetic data. For example, bit arrays, real number vectors, and trees are common data structures that we can merge again via crossover.

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