Optimal Design of Landscape Space Environment Based on Interactive Genetic Algorithm

In order to solve the challenges of landscape space environment optimization design, in view of the shortcomings of the existing dynamic programming algorithms, this study introduces an innovative spatial environment optimization design method based on interactive genetic algorithm. The new scheme uses the principles of natural selection theory to accurately identify and locate key influencing factors, and accordingly makes a sensible classification of indicators to reduce possible interference. At the same time, using the unique mechanism of interactive genetic algorithm, this scheme cleverly constructs a design strategy for landscape space environment optimization. The empirical results show that the proposed scheme shows significant improvement compisd with the traditional dynamic programming algorithm in terms of the accuracy of the optimal design of the spatial environment and the processing efficiency of key factors, showing its obvious strong advantages. In the landscape landscape, the spatial environment optimization design plays a vital role, which can accurately predict and optimize the growth trend and output results of the landscape spatial environment optimization design. However, in the face of complex simulation tasks, traditional dynamic programming algorithms show some inherent shortcomings, especially when dealing with multi-level challenges, their performance is often unsatisfactory. To overcome this problem, this study introduces a new idea of spatial environment optimization design optimized by interactive genetic algorithm, which accurately controls the influencing parameters through the theory of natural selection, and uses this as a road map for index allocation, and then uses interactive genetic algorithm to innovate and construct a system scheme. The test results clearly point out that in the context of the evaluation criteria, the new scheme has been significantly optimized in terms of accuracy and processing speed for a variety of challenges, showing stronger performance superiority. Therefore, in the process of optimizing the design of landscape space environment, the simulation scheme based on interactive genetic algorithm successfully overcomes the shortcomings of traditional dynamic programming algorithms, and significantly improves the accuracy and operation efficiency of simulation.