In this paper, we examine the combination of quantum chemical methods with optimization techniques for molecular design. A simple hydrofluorocarbon refrigerant design example and a solvent design example illustrate the proposed framework. The hydrofluorocarbon compounds are optimized for their heats of formation, and the potential solvents are searched for capacity, selectivity, and environmental safety. In both examples, a genetic algorithm is applied to generate and screen candidate molecules. The molecular properties are evaluated using a combination of quantum chemical calculations and group contribution methods. We assess the feasibility of the proposed approach for small molecules and find that establishing a proper tradeoff between the accuracy of the quantum chemical method and computational expense is vital.