🔴 Three Parent CrossOver Python Code || Genetic Algorithm PYTHON Language 🚀 🚀
#ThreePointCrossover In Genetic Algorithm
#ThreePointCrossover
In the Cross Over Genetic Algorithm, child is generated by matching the first two-parent and if the bit from 1st parent doesn't match with 2nd parent then the bit will be replaced by the 3rd parent.
#Genetic Algorithm: The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that are based on natural selection, the process that drives biological evolution. The genetic algorithm repeatedly modifies a population of individual solutions.
#SinglePointCrossover: A crossover point on the parent organism string is selected. All data beyond that point in the organism string is swapped between the two parent organisms. Strings are characterized by Positional Bias.
#Two-PointCrossover: This is a specific case of an N-point Crossover technique. Two random points are chosen on the individual chromosomes (strings) and the genetic material is exchanged at these points.
#Shuffle crossover
Shuffle Crossover selects the two parents for crossover. It firstly randomly shuffles the genes in both parents but in the same way. Then it applies the 1-Point crossover technique by randomly selecting a point as a crossover point and then combines both parents to create two offspring.
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