I need to use discrete differential evolutionary algorithm for assigning discrete values from set size $L$ to vectors of size $D$ where $L$ could be smaller, equal or larger than $D$. Elements of vector $X$ could take the same values of other elements.  My question is if we have a population of size $NP$ with each vector $X$ in the population of size $D$. How do we actually apply the mutation operand:$$V_{j,i}^{G+1} = X_{j, r_1}^{G} + F\cdot (X_{j, r_2}^{G}-X_{j, r_3}^{G})$$where $i$, $r_1$, $r_2$, $r_3$ are references to vectors in $NP$ and none is equal to the other, $J$ is an index in vector $X$, and $F$ is a random number between $0$ and $1.2$.Suppose $X_{r_1}^{G}$ is equal to $\{4, 1, 3, 2, 2, 0\}$ and  $X_{r_2}^{G}$ is equal to $\{2, 2, 3, 0, 4, 2\}$ and $X_{r_3}^{G}$ is equal to $\{1, 2, 3, 3, 0, 1\}$Could anyone explain in detail the steps (through example if possible) on how to get the mutant vector $V_{j,i}^{G+1}$
Mutation and crossover operations in discrete differential evolutionary operations?
algorithms;optimization;heuristics;evolutionary computing