This paper presents the use of genetic algorithms to develop smartly tuned fuzzy logic controllers in multicriteria complex problems. This tuning approach has some specific restrictions that make it very particular and complex because of the large time requirements existing due to the need of considering multiple criteria ---which enlarges the solution search space---, and to the long computation time models usually used for fitness assessment. To solve these restrictions, two efficient genetic tuning strategies considering different multicriteria approaches have been developed and tested in a real-world problem for fuzzy control of HVAC Systems.