In your example, you have a size_t or double factor for array growth. If you set it to -1, you would have an unpleasant time. You need a way to specify the range of valid values. In more complex algorithms, you need a way to evaluate several parameters together to determine if they are valid.
Since you're not always optimizing for the same thing (time vs memory; wasted memory vs number of reallocations; for approximation algorithms, how good an approximation is generated), you need a way to specify that as well. Putting that in the language would be horribly complex. It would be much simpler for everyone if it were in a library instead. I could probably code up a basic version in a couple hours. Which I'll do for US$150 -- below market rate, especially since I'd continue supporting it. Furthermore, your idea of changing compile-time constants without recompiling the program is unworkable. Constants are folded and inlined. That "* 2" might turn into "<< 1". A loop based on a constant can be unrolled. You suggested that we can do a random walk on values to find optimal values. This will find a local minimum, which might not be the globally optimal value. Something like simulated annealing would work better in the general case. Simulated annealing is a fair bit more complex than a random walk; it's not going to be implemented inside druntime.
