Low-carbon optimization of spatial pattern in Shenfu New District based on genetic algorithm

Abstract

The realization of low-carbon development is the key to solving the global climate change problem. China’s total carbon emissions share in the world is increasing year by year. Taking the road of low-carbon city development is the inevitable trend of China’s city development in the future. Increasing the concentration of urban land space can improve energy utilization and achieve the optimal goal of energy conservation and emission reduction. Genetic algorithm is a method to search the optimal solution by simulating the natural evolution process, providing a scientific solution for low-carbon city planning. This paper starts with the spatial arrangement of land use, minimizes people’s spatial travel distance through the global optimization ability of genetic algorithm. It summarizes the low-carbon spatial organization characteristics of Shenyang-Fushun New City, explores the analysis method of urban spatial low-carbon pattern, puts forward the optimization strategies of urban spatial structure, urban transportation network, green space system and low-carbon industrial layout, adjusts the development trend of urban areas, promotes low-carbon living and production behaviours, and provides theoretical basis and practical experience for the planning of low-carbon cities.