Optimization of Urban Landscape Design Based on Interactive Genetic Algorithm

To meet the dynamic needs of smart city landscape design, the interactive genetic algorithm (IGA) was introduced to enhance the efficiency and adaptability of the design process. Key design parameters were defined as genes, and a fitness function was constructed. The study combined genetic algorithm operations (selection, crossover, mutation) with user interface feedback for algorithm adjustment and multi-objective optimization. The results showed a significant enhancement in urban landscape design capabilities, with designer ratings reaching as high as 9.1 out of 10, and local search optimization requiring only 0.08 hours. This method improved urban landscape design, emphasizing the importance of applying adaptive and user-centric approaches in urban planning. By integrating user preferences and environmental considerations, it ensured a sustainable and aesthetically pleasing urban environment, contributing to the development of smart cities.