A crossover operator is a genetic operator in genetic algorithms that combines two parent solutions to generate a new offspring solution. It is inspired by biological crossover or recombination processes in which genetic information is exchanged between chromosomes during meiosis.
In a crossover operator, two parent solutions are selected, and a crossover point is chosen randomly. The new offspring solution is created by combining the genetic information from both parents, either by swapping the genetic material before or after the crossover point, or by using a combination of both methods.
The crossover operator is an essential process in genetic algorithms, as it allows the search algorithm to explore different areas of the solution space and potentially discover new optimal solutions.
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