# Is there a name for this approach to evolutionary algorithms?

I am considering an approach to evolutionary algorithms, in which instead of maintaining a population of individuals, we maintain a pool of $$N$$ mutations that can be applied to a base genome. For every possible subset (or many possible subsets) of the mutation pool, we apply that subset to the base genome to produce an individual, then test that individual. We discard mutations for which the population with that mutation performs worse than the population without it. We merge the best-performing mutations into the base genome for the next generation. Then we replace the discarded or merged mutations with new ones.

Is this known under some name? Is it a good idea?

• When you say "a pool of $N$ mutations", do you mean changes that you can apply to the "base genome"? Then you say "We discard mutations for which the population with that mutation performs worse than the population without it", so does it mean that you will evaluate, say, $M$ individuals that are produced by $M$ sets of mutations (on set of mutations produces an individual) and then compute the fitness of the whole population rather than of individuals?
– nbro
May 12, 2021 at 8:53
• @nbro fitness of a particular mutation would be measured by the average performance across all individuals with the mutation, minus the average performance across all individuals without the mutation. May 12, 2021 at 8:58
• But if you have a base genome and apply the same mutation multiple times to that base genome, you will get multiple mutated individuals that are identical. In your case, it seems you maintain only one individual from one generation to the other. However, you apply different subsets of the set of possible mutations to that base individual to produce different intermediate individuals. So, you want to calculate the "fitness of a mutation", i.e. how good it might be if applied?
– nbro
May 12, 2021 at 9:01
• @nbro that is one way to put it. May 12, 2021 at 14:16