Conditional Parameter Optimization solution needed

Hello Everyone

I have a problem in optimization passes. I've searched a lot but non of questions nor the answers in the forum was the
one solving this problem.

The problem is that i have some bool parameters in my inputs which when they are set as false there is
no need to optimize some other parameters.

for example if the "Psar_Active" parameter is set to false my EA won't use Parabolic SAR indicator  in it's decision making process,
so optimizing the "step" and "max"  (two other input parameters) of the indicator is useless (only when the Activation parameter is false).

unfortunately i couldn't find a way for this. so many of the optimization results are useless
and this make the whole optimization much less effective.

Lets assume that "Step" Parameter has 5 steps and "Max" Parameter has 4 steps the total steps considering the
"Psar_Active" parameter (which has two steps) is currently resulting to 40 passes (5*4*2), which 19 of them are useless
(the ones with "Psar_Active" ==false). if this problem could be solved the total passes should be reduced to 21 (5*4*1+1).

I'm not sure which way will do but i assume that writing a function in the ontester sections with two parameters that
 one of the is them input parameter of EA and the other one a boolian parameter which determines the necessity of optimization
(or any solution that changes the total number of passes in optimization) can solve this problem.

The solution should be able to solve the problem for multiple parameters.

for example if the Psar_Active==false Parameters Step & Max should not be optimized
but at the same time ADX_Active==true Parameters Period & Min should be otimized.

so if number of passes are as folow 

Psar_Active 2

Step_Psar 5

max_Psar  4

ADX_Active 2

Period_ADX 3

Min_ADX 4

the total passes should be [(1*5*4+1)*(1*3*4+1)]=273

I would be great-full if we can figure this out. thank in advance for your help.