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The crossover rate, $p_c \in [0, 1]$, is a hyper-parameter that controls the rate at which solutions are subjected to crossover. So, the higher $p_c$, the more crossovers you perform, so the more diversity (in terms of solutions/chromosomes) you may introduce in the population. Typical values of $p_c$ are in the range $[0.5, 1.0]$. For example, in this ...


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If X is your 6D vector and m(X) is the mutated version of X, then you can renormalise the mutant back to unity by dividing by the sum of X, i.e. X' = m(X)/sum(X). However, I encourage you figure out how to mutate a vector while keeping the length of the vector at 1. One way to do this would be to randomly rotate your vector in 6D space. The length should ...


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