My algorithm has 2 variables , illumination level and cooling capacity, the lower and upper bounds are as follows: lb =[200,1.8]; ub =[500,17.5].
The objective function relies on these two variables to calculate the energy consumption of lighting and cooling and I'm using quadratic penalties.
After simulating the code on MATLAB , the best objective is a huge number and remains the same over 100 iterations.
I've tried to change the inertia weight,cognitive and social coefficient,but the results remain the same.
Therefore I would like to know if there are any things that I should consider in my algorithm to have relatable results.
Dear Hiba
You can easily solve this problem with SIMUS, using two criteria for Illumination level, and other two criteria for cooling capacity.
The first criterion for illumination puts as a target the minimum value (200), specifying that the illumination must be equal or greater that 200
The second equation for illumination must call for the
maximum value (500), that is, specifying that illumination must be less that 500
In both cases the left side of the two equations are identical, but changing the math symbol (> or =) to 200 and (= 1.8 and < = 17.5).
Since in SIMUS these four variables are considered simultaneously, they must interrelate, and the result is the consequence of these multiples interactions.
Of course you may add as many criteria relative to health, economics , environment, etc. as you want
In my opinion you do not need to put any penalty for this, because the result cannot surpass the respective lower and upper bounds.
If you need help I will very pleased in answering your questions
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