A Holistic Optimization Approach for Landscape Spatial Layout Based on Neighborhood Algorithms

Abstract

In the face of accelerating urbanization and environmental sustainability, this study proposed an overall optimization method of landscape pattern spatial layout based on simulated annealing algorithm (SA). Aiming at the problems of low efficiency and difficult optimization of traditional design mode under complex environmental conditions and diversified user needs, automatic intelligent optimization of spatial layout is realized through algorithm driven. Firstly, a multi-objective optimization system was constructed to integrate core indicators such as environmental aesthetics, functional zoning and ecological benefits, and a quantitative evaluation mechanism was established by combining GIS geographic data and user behavior model. The algorithm simulates the minimization principle of material cooling energy, dynamically adjusts the spatial planning scheme in the process of iterative optimization, and gradually approaches the optimal solution satisfying multiple constraints. Several groups of cases have verified that compared with traditional design methods and other optimization algorithms, this method not only improves the scheme generation efficiency by 37%, but also increases the environmental quality index by 22% and user satisfaction by 18%, successfully realizing the collaborative optimization of aesthetic value, functional requirements and ecological benefits. It is also found that the algorithm can derive a personalized design scheme through parameter adjustment, which provides a new path for design innovation. The results not only provide an efficient decision-making tool for the field of landscape design, but also its algorithm framework has universal reference value for spatial optimization problems such as urban planning and building layout, demonstrating the technical advantages of intelligent algorithms in complex system design.