To assure maximum economic benefits and the energy performance of solar water heating systems, the proper sizing of components and operating conditions need to be optimized. In recent years, a number of studies to design optimally solar water heating systems have been tried. This paper presents a design method for optimizing the various capacity-related and installation-related design variables based on life cycle cost using a genetic algorithm. The design variables considered in this study included the types and numbers of solar collector and auxiliary heaters; the types of storage tanks and heat exchangers; the solar collector slope; mass flow rates of the fluid on the hot and cold sides. The suggested method was applied for optimizing a solar water heating system for an elementary school in Seoul, South Korea. In addition, the effectiveness of the proposed optimization method was assessed by analyzing the obtained optimal solutions of six case studies, each of which was simulated with different solar fractions. It is observed that a trade-off between the equipment cost and the energy cost results in an optimal design that yields the lowest life cycle cost. Therefore, it could be helpful to apply the optimal solar water heating system by comparing the various design solutions obtained by using the optimization method instead of the engineer's experience and intuition.