Indoor Space Layout Design based on Differential Evolution Algorithm

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Sha Meng


To enhance the interactivity of spatial design, this study proposes an indoor spatial layout design method based on differential evolution algorithm, which combines backtracking strategy and reverse learning strategy to improve the interactive differential evolution algorithm. The experimental data demonstrated that the proposed method for indoor space layout design achieved an average user satisfaction of 81.7%, which increased by 16.8% compared with traditional interactive genetic algorithms. In addition, the improved human-computer interaction interface scored higher than 0.8 in terms of usability, reliability, customizability, and interactive feedback. This means that the improved interface can better meet user needs and provide a better user experience. This study shows that the indoor space layout design method ground on differential evolution algorithm and the improved human-computer interaction interface can significantly improve user satisfaction and user experience. This has brought more efficient and convenient solutions to the field of spatial design.

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Special Issue - Data-Driven Optimization Algorithms for Sustainable and Smart City