Uh-huh. Now, what does that remind me of ?
Ignoring the discussion about the OP for a while, and talking about generalities:
Both are iteritive processes, and thus both show "improvement" over time.
However in evolution, a failure to reproduce is negative information (there isn't
really even the instruction "don't try that again". It is just that successes are all that are copied).
In engineering, people often make test structures that are designed to test particular aspects of their designs, these failures are then analysed, and then future designs are altered in light of the information received from these experiments.
Also, if an engineering artifact fails in use, often (usually), this failure is analysed to determine why it failed,
so that remedial action can be taken.
This is not analogous to any process in evolution.
Similarly, if a set of experiments are designed
with the express purpose of finialising particular design parameters, then I wouldn't class the [process determining the] resulting parameters as having any similarity to [a process that leads to] informaton that has arisen due to random mutation.
Of course evolutionary algorithms are analogous
to much of evolution, however, I would argue that one has to be clear about the fundamental differences beween the selection algorithms used in these algorithms and the process of natural selection.
The difference is self-replication, which means that one doesn't need any slection algorithm, as the mere act of reproduction or not
is the selection procecss.
In brief:
Evolution requires the equivalents of both variation and natural selection.
Variation arises in any process where imperfect copies are made.
Natural selection arises in any process where (perfect or imperfect) self-replication occurs.
Evolutionary algorithms, because the products are not self-replicating, require some imposed selection process, either intelligent choice or algorithmic.
However, they can demonstrate the power of evolutionary
approaches.