What is the best way to pick the optimized configuration from this dataset? I have about 8000 configurations in an excel sheet. each configuration has four scores as seen in the image below. I would like to choose the best solution that has the highest lighting level score, lowest energy consumption score, the highest visual comfort score, the highest thermal comfort score, and the lowest CO2 level score. I'm new to data science but familiar with Python. I'm hoping that someone who is kind enough to explain a possible solution to rank these configurations from best to worst. Also, I'm interested to know the mathematical algorithm behind of the possible ranking system.
I have not executed the below code but I would do something like this,
df.loc[(df['Lighting Levela (Max)'] == max(df['Lighting Levela (Max)']) &amp;
       (df['Energy Consumption (Min)'] == min(df['Energy Consumption (Max)']) &amp;
       (df['Visual Comfort (Max)'] == max(df['Visual Comfort (Max)']) &amp;
       (df['Thermal Comfort (Max)'] == max(df['Thermal Comfort (Max)']) &amp;
       (df['CO2 levels (Min)'] == min(df['CO2 levels (Max)']), :)