A multi-objective design optimization strategy for vertical U-tube ground heat exchangers (GHEs) is presented to minimize the system upfront cost and entropy generation number simultaneously. Five design variables of vertical U-tube GHEs, including borehole number, borehole depth, borehole radius, U-tube outer radius and fluid mass flow rate, are first selected via a global sensitivity analysis method, and then optimized by a genetic algorithm (GA) optimizer implemented in MATLAB. Based on the Pareto frontier obtained from the GA optimization, a decision-making strategy is then used to determine a final solution. Two case studies are presented to validate the effectiveness of the proposed strategy. The results based on a small scale GSHP system in Australia show that, compared to the original design, the use of this proposed strategy can decrease the total system cost (i.e. the upfront cost and 20 years' operating cost) by 9.5%. Compared to a single-objective design optimization strategy, 6.2% more energy can be saved by using this multi-objective design optimization strategy. The result from a relatively large scale GSHP system implemented in China shows that a 5.2% decrease in the total system cost can be achieved by using this proposed strategy, compared with using the original design.