Intelligent Indoor Layout Design Based on Interactive Genetic and Differential Evolution Algorithms

Abstract

As the real estate industry expands with time, the personalized needs of users for indoor space layouts have become increasingly complex. Traditional indoor space layout design methods can no longer meet the needs of large market groups because of their complex steps and low levels of specialization. Therefore, this study first analyzes the problematic factors in indoor space layout design. Second, an interactive genetic algorithm is introduced to solve the multifactor optimal selection problem; the process is optimized and improved using a differential evolution algorithm. A comprehensive spatial layout model combining interactive genetic and differential evolution algorithms is proposed. The experimental results show that the model performs best with uniform variation, and its average number of iterations to find the optimal individual is 57. In addition, compared with similar layout models, the proposed model achieved the highest space utilization value of 79%, which is approximately 19% higher than that for the stacking layout model; it also required the shortest time, that is, 15 min. In summary, the proposed model provides a new intelligent method for indoor layout design, which is expected to improve the satisfaction of designers and users.