In an optimisation problem, there is an objective function and, often, a set of constraints. You are trying to find the best solution from all possible solutions. The objective function itself reveals preferences ('best' solution --- isn't that subjective?), and this is sometimes inherent, sometimes explicit.

I use the word 'optimisation' in its mathematical sense. And I know the difference between definitions and axioms. Objective functions are definitions, not axioms. You can't take them as facts! In an optimisation problem, you start with an objective function given a set of constraints, and then you arrive at an optimal solution and work it out. This is the real optimisation process. You, on the other hand, observe a phenomenon, and then explain it by giving it an objective function as a theory... although the phenomenon isn't efficient in giving the optimal outcome.

I'm pretty sure you're still not using the word "optimization" in the sense of the phrase "optimization process" as used on Less Wrong. An optimization process doesn't have to be a process that maximizes an explicitly-defined utility function; the function can be implicit in its structure or behaviour.

It's not really the same as the sense of "optimization" described in the aforelinked Wikipedia article, which isn't the subject of this discussion post. The terminology of "optimization processes" is used to analyze dynamics acting within a system.