Let's say I'm optimizing something. To pick an arbitrary example, let's say I'm choosing the shape of some part to maximize strength-to-weight ratio. So I get some FEM software, parametrize the shape, and run gradient ascent or whatever to find the optimum shape.
When I do this procedure, I would generally expect that the calculated optimal strength-to-weight ratio is an overestimate of the actual strength-to-weight ratio for that shape---especially if I'm running the FEM software at low accuracy. Basically, the optimization algorithm will seek out and exploit any inaccuracies in the software to create impossibly high performance metrics.
In the context of economics, this basic insight is famously known as Goodhart's Law. In the context of optimization, how do people refer to this? Is there a term for it? Is there a paper or textbook that I can cite that discusses it?