In the 1970s, when card-sort conjoint was the norm, researchers didn't worry about this. Only one card might be evaluated at a time (and a rating was given), yet the researcher might put multiple products in the market simulator. (Of course there were problems getting the scale factor right...more on this below.)
In the 1980s, when ACA was the norm, only two products were ever shown at a time in the tradeoff questionnaires, and yet dozens could be specified at a time in the market simulations. (Again, with problems getting the scale factor right...again, it's coming.)
With the use of CBC and proper MNL modeling (with its appropriate error theory), researchers have become more aware that context matters to choice. There are many types of context effects, but one of the stronger ones is the effect of increasing the number of concepts per task on response error.
One can tune the response error in the simulator by manipulating the "exponent" (the scale factor), to try to adjust for the fact that as the number of concepts grows, the response error increases. (Tuning the exponent makes the resulting shares of preference flatter or more extreme.) But, unless you've actually fielded CBC questions with different numbers of concepts shown, you don't know exactly the right scale factor to use under different conditions.
As a result, the general recommendation is to try not to stray too far in market simulations from the dimensions of the CBC tasks shown during data collection.