(C++) Solution to do a flexible parameter optimization with start-step-stop-schema
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(C++) I need a good solution to do a flexible parameter optimization with start-step-stop-schema.
A function should run through all possible combinations of selected parameters (bruteforce) to find the combination of variables that produce the highest value of return.
The start-step-stop optimization rules are defined in a map for double and integer parameter settings. Look at the file [login to view URL]
The five settings for each variable are:
1. Optimization of this variable is activated (true or false). When false always as pre-set. When true than optimize in kombination with all other activated parameter-variables.
2. Value (e.g. = 5) (This value is set according to the rules and goes every pass to the function)
3. Start value (e.g. start = 0)
4. Step value (e.g. step = 7)
5. Stop value (e.g. stop = 100)
combination example:
int_parameter[“Var1“] = {true, 5, 0, 7, 100} // → 15 values (0,7,14,21,28,35,42,49,56,63,70,77,84,91,98)
int_parameter[“Var2“] = {true, 5, 100, 50, 235} // → 3 values (100,150,200)
double_parameter[“Var3“] = {false, 5, 0.5, 0.2, 0.7} // → 2 values (0.5,0.7)
double_parameter[“Var4“] = {true, 5, 33.11, 10.11, 69.24} // → 4 values (33.11,43,22,53,33,63,44)
In this example the kombinations of Var1, Var2, Var4 should be optimize (only those who are true).
Var1*Var2*Var4 → 15*3*4 = 180 possible combinations. In this example the function is to be executed 180 times with the different combinations.
It would be fine to use dlib ([login to view URL]) but I do not know whether “bruteforce with start step stop schema”-method is suitable with that. You can check it please and you also can code your own solution if dlib is not suitable for this purpose.
Important is, that the solution is flexible and can deal with different number of variables and combinations. (No rigid loop in loop... logic). Therefore, the solution must work with different number of variables and combinations.
Thank you for looking, I look forward to hearing from you
if the function somehow smooth, it's unnecessary to do brute-force. Your task is called global optimization problem. I have plenty of experience with it.
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