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#TwoPointCrossover In Genetic Algorithm #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. #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. #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. #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. Hope you guy's Like my Video if is so then Subscribe to my channel my youtube:: / @thenoblepriest9863 my Facebook: https://www.facebook.com/profile.php?... my Instagram ID:: / priest.dev