![]() From there you can run subsequent optimizations where you increase the complexity. From there you’ll have a good idea where your final solution will lies so you can either lock down those parameters or significantly limit their range. That definition should be able to run really fast and be controlled by only a few variables. I’d start with a very simplified structural setup with only the key members in place. I would recommend breaking the optimization problem up into bite size pieces. I also found that if the algorithms that are affected by sliders are smooth in their change, the solvers have a much better chance to converge on a solution. You go from looking for a point on a meter stick, to a point on a map to a needle in a haystack, etc. Remember that for each slider you’re adding, you’re increasing the dimension of the solution space. Your problem is that the scope of search is too big and the calculation time for each attempt is probably very had some good recommendations about the sliders. I think a general shape is being described but some detail members are also worked out at the same time. However, it looks like your definition is doing a lot at the same time. ![]() Hi there, I wasn’t able to fully understand what your definition does as I don’t have Karamba on my machine.
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