Solar air conditioners (A/Cs) have attracted much attention in research, but their performance and cost have to be optimized in order to become a real alternative to conventional A/C systems. In this study, a hybrid solar A/C is simulated using the transient systems simulation program(trnsys), which is coupled with matlab in order to carry out the optimization study. The trnsys model is experimentally validated prior to the optimization study. Two optimization problems are formulated with the following design variables: solar collector area, solar collector mass flow rate, solar thermal energy storage volume, and solar electrical energy storage size. The genetic algorithm (GA) is selected to solve the single-objective optimization problem and find the global optimum design for the lowest electrical consumption. To optimize the two objective functions simultaneously, energy consumption and total cost (TC), a multi-objective genetic algorithm (MOGA) is used to find the Pareto curve within the design variables' bounds while satisfying the constraints. The overall cost of the optimized solar A/C design is also compared to a standard vapor compression cycle (VCC). The results show that coupling trnsys and matlab expands trnsys optimization capability in solving more complex optimization problems. The results also show that the optimized solar hybrid A/C is not very competitive when the electricity prices are low and no governmental support is provided.