Implementation of improved shuffled frog leaping algorithm for optimum landscape space environment design

Abstract

Abstract Landscape design is a complex process, requiring the seamless integration of various elements such as the senses, environment, morphology and optimization techniques. In this study, a new approach called the Interactive Enhanced Shuffled Frog Leaping Algorithm (IISFLA), specifically has been designed to optimize spatial environments in landscape design. The IISFLA is a hybrid optimization method that combines the Shuffled Frog Leaping Algorithm (SFLA), Bacterial Foraging Algorithm and human–computer interaction to address intricate nonlinear challenges. To demonstrate its effectiveness, IISFLA has been applied in the design of a garden community and contrasted with conventional design of landscape methodologies. To tackle the problem at hand, a optimality model of search that is layer-by-layer, which allows us to divide the problem space into manageable subsolution spaces, has been employed. Also, a participatory evaluation strategy has been adopted to assess the impact of the landscape design on different user groups. The results of this study reveal that IISFLA surpasses conventional methods in terms of performance and user satisfaction, making it a versatile and user-friendly tool for landscape designers. The research emphasizes the innovation, significance and implications of our work in the field of landscape design and optimization. Key numerical findings include a 22.6% increase in landscape space evaluation value when using IISFLA compared to traditional methods, a 34.7% reduction in computational time and a 28.9% improvement in user satisfaction rates. These outcomes highlight the effectiveness and potential of IISFLA in enhancing landscape design outcomes.