Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India

Research Article

Exploration on Ant Colony Optimization for Optimizing Land Use Spatial Allocation

Download91 downloads
  • @INPROCEEDINGS{10.4108/eai.17-11-2023.2342818,
        author={Dagang  Si and Lei  He},
        title={Exploration on Ant Colony Optimization for Optimizing Land Use Spatial Allocation},
        proceedings={Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India},
        publisher={EAI},
        proceedings_a={ICSETPSD},
        year={2024},
        month={1},
        keywords={ant colony optimization land use spatial optimization upper reaches of the yellow river},
        doi={10.4108/eai.17-11-2023.2342818}
    }
    
  • Dagang Si
    Lei He
    Year: 2024
    Exploration on Ant Colony Optimization for Optimizing Land Use Spatial Allocation
    ICSETPSD
    EAI
    DOI: 10.4108/eai.17-11-2023.2342818
Dagang Si1,*, Lei He1
  • 1: School of Surveying and Geographic Information, Lanzhou Resources & Environment Voc-Tech University, Lanzhou 730000, Gansu, China
*Contact email: sdg0212@163.com

Abstract

The purpose of optimizing the allocation of land use (LU) space is to enable effective utilization of land resources in various regions, in order to maximize the economic and social benefits of limited land area. The upper reaches (UR) of the Yellow River are important agricultural production bases and ecological barriers in China, and optimizing land space is of great significance for promoting agricultural development and protecting the ecological environment. Therefore, the optimization method based on ant colony optimization (ACO), as a new type of optimization algorithm, has strong adaptability, robustness, and global search ability, which can effectively solve the problem of LU spatial optimization configuration. This article determined the definition and constraints of land issues, and set relevant parameters. The steps of the ACO were analyzed, and the results of the algorithm were analyzed and evaluated. The LU situation in the UR of the Yellow River was analyzed using survey methods and statistical analysis. The results showed that the patch density index before and after optimization in various regions was generally small, with the index values of forest land and construction land being 0.1142 and 0.2975, respectively.