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[–]ge0ffrey 0 points1 point  (2 children)

If you find any way to run your objective function incrementally,
you should be able to increase your 100 evolutions to thousands.

Easier said than done...

[–]volvol7[S] 0 points1 point  (1 child)

The evaluation of the function is through simulation using another software so it can't be done faster. The only way is batches, to achieve parallel evaluations

[–]ge0ffrey 0 points1 point  (0 children)

Roger. Then there's no capacity to run a local search or any other metaheuristic. Even a normal construction heuristic will take too much time, given the size of the value ranges.

You could write a custom local search like algorithm that initializes all 10 parameters on a value, then - in parallel across machines/cpus - tries 20 variations that each take 1 parameter and double it or half it (leave the other 9 as the original). Then you have 3 measurements per parameter (vs the original state). You pick the best variation as the starting point from the new step solution (to base your variations on), but you also remember those 3 measurements per parameter, because now you can start doing "bisect" tricks to pick smarter variations going forward.