Graphical User Interfaces (GUIs) play a pivotal role in human-computer interaction, demanding a design approach that carefully balances usability, performance, and system resource efficiency. This study introduces a novel method using Genetic Programming (GP) to optimize the selection and arrangement of GUI elements with a dual focus on enhancing user experience and minimizing memory consumption. The GP-based approach simulates natural evolutionary processes through operations such as selection, crossover, and mutation, allowing the iterative refinement of GUI designs over successive generations. A fitness function, which evaluates both usability metrics (e.g., layout intuitiveness, interaction ease) and technical performance (e.g., memory usage), guides the evolutionary process. This optimization technique supports sustainable interface design by lowering hardware demands, making it suitable for deployment in resource-constrained environments while simultaneously improving user satisfaction and accessibility. Experimental results demonstrate that the proposed method successfully generates GUI configurations that are not only user-friendly but also highly efficient in terms of memory footprint.