The urban design process is complex and interdisciplinary, especially in the context of high-density cities with high-rise buildings. The design of high-rise buildings requires input from a variety of stakeholders in the city, who often represent conflicting requirements and interests. However, conventional design approaches struggle to address this complexity. This study introduced a generative urban design approach and applied it to a case study for high-rise urban development in Guangzhou, China. Specifically, 7500 urban forms were generated with variables such as street networks, block offset, building typology, and green space, and then were evaluated and optimized via multi-objective evolutionary algorithms. A total of 30,000 performance values were generated through various simulations. This study also presented a two-round, quantitative evaluation process against eight performance objectives from environmental, social, and economic aspects, including urban density, green space area, Daylight Potential, construction cost, Heat Stress, Green Space Accessibility, View Interest, and Shadow Impact.