intro to genetic algorithms, main principles (selection, crossover, mutation), features of the method, overview of basic algorithm by way of an example
You need to select a parameter beforehand that defines the probability of mutation, e.g., 5%. So for example you'ed randomly generate numbers from a uniform distribution for each bit (p) and if p < 0.05 you flip the bit, otherwise you leave the bit as is.
Sir. What do you mean by threshold in mutation?
You need to select a parameter beforehand that defines the probability of mutation, e.g., 5%. So for example you'ed randomly generate numbers from a uniform distribution for each bit (p) and if p < 0.05 you flip the bit, otherwise you leave the bit as is.