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The Application of Genetic Algorithm in Land Use Optimization Research: A Review

Author

Listed:
  • Xiaoe Ding

    (School of Information Engineering, China University of Geosciences (Beijing), Beijing 100083, China)

  • Minrui Zheng

    (School of Public Administration and Policy, Renmin University of China, Beijing 100872, China)

  • Xinqi Zheng

    (School of Information Engineering, China University of Geosciences (Beijing), Beijing 100083, China
    Technology Innovation Center for Territory Spatial Big-Data, MNR of China, Beijing 100036, China)

Abstract

Land use optimization (LUO) first considers which types of land use should exist in a certain area, and secondly, how to allocate these land use types to specific land grid units. As an intelligent global optimization search algorithm, the Genetic Algorithm (GA) has been widely used in this field. However, there are no comprehensive reviews concerning the development process for the application of the Genetic Algorithm in land use optimization (GA-LUO). This article used a bibliometric analysis method to explore current state and development trends for GA-LUO from 1154 relevant documents published over the past 25 years from Web of Science. We also displayed a visualization network from the aspects of core authors, research institutions, and highly cited literature. The results show the following: (1) The countries that published the most articles are the United States and China, and the Chinese Academy of Sciences is the research institution that publishes the most articles. (2) The top 10 cited articles focused on describing how to build GA models for multi-objective LUO. (3) According to the number of keywords that appear for the first time in each time period, we divided the process of GA-LUO into four stages: the presentation and improvement of methods stage (1995–2004), the optimization stage (2005–2008), the hybrid application of multiple models stage (2009–2016), and the introduction of the latest method stage (after 2017). Furthermore, future research trends are mainly manifested in integrating together algorithms with GA and deepening existing research results. This review could help researchers know this research domain well and provide effective solutions for land use problems to ensure the sustainable use of land resources.

Suggested Citation

  • Xiaoe Ding & Minrui Zheng & Xinqi Zheng, 2021. "The Application of Genetic Algorithm in Land Use Optimization Research: A Review," Land, MDPI, vol. 10(5), pages 1-21, May.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:5:p:526-:d:554597
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    1. Chuchu Zhang & Peng Wang & Pingsheng Xiong & Chunhong Li & Bin Quan, 2021. "Spatial Pattern Simulation of Land Use Based on FLUS Model under Ecological Protection: A Case Study of Hengyang City," Sustainability, MDPI, vol. 13(18), pages 1-18, September.
    2. Tingting Pan & Fengqin Yan & Fenzhen Su & Vincent Lyne & Chaodong Zhou, 2022. "Land Use Optimization for Coastal Urban Agglomerations Based on Economic and Ecological Gravitational Linkages and Accessibility," Land, MDPI, vol. 11(7), pages 1-18, July.
    3. Xujing Yu & Liping Shan & Yuzhe Wu, 2021. "Land Use Optimization in a Resource-Exhausted City Based on Simulation of the F-E-W Nexus," Land, MDPI, vol. 10(10), pages 1-22, September.
    4. Xinxin Fu & Xiaofeng Wang & Jitao Zhou & Jiahao Ma, 2021. "Optimizing the Production-Living-Ecological Space for Reducing the Ecosystem Services Deficit," Land, MDPI, vol. 10(10), pages 1-17, September.

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