Construction and Optimization of Forestry Economic Model Based on Genetic Algorithm

The purpose of this paper was to explore how to use genetic algorithm to build and optimize forestry economic model. At present, forestry economic model is of great significance in decision-making, resource allocation and ecological environment protection. However, there are some problems in the existing forestry economic model, such as incomplete model construction, inaccurate parameter estimation, unreasonable optimization method, etc. Therefore, this study hoped to further optimize and improve the forestry economic model by introducing genetic algorithm, so as to improve the prediction ability and decision-making effect of the model. This paper focused on the construction and optimization of forestry economic model, combining with genetic algorithm for in-depth research. Firstly, the research status and existing problems of forestry economic model were introduced, as well as the application status and development trend of genetic algorithm in optimization problems. Then it discussed the basic theory and model framework of forestry economic model construction in detail, as well as the construction and parameter estimation methods of forest growth model, economic model, and environmental model, and finally realized the integration of forestry economic model. Then, the basic concepts and principles of genetic algorithm were introduced, including encoding and decoding methods, crossover, mutation, selection, and other operations. On this basis, the optimization of forestry economic model based on genetic algorithm was discussed in detail, including the determination of optimization objectives and constraints, the application method of genetic algorithm, and the analysis and evaluation of optimization results. In the experiment of plant growth, it can be known that the optimized forestry economic model has better feasibility and economic benefits. To sum up, this study, combined with genetic algorithm, deeply discussed the construction and optimization of forestry economic model, and made certain research achievements and contributions. At the same time, it also provides a reference for the further study of forestry economic model in future.