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Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China

Author

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  • Xiaoya Ma

    (School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China
    These authors contributed equally to this work.)

  • Xiang Zhao

    (School of Resource and Environmental Science, Wuhan University, Wuhan 430079, China
    These authors contributed equally to this work.)

Abstract

As the main feature of land use planning, land use allocation (LUA) optimization is an important means of creating a balance between the land-use supply and demand in a region and promoting the sustainable utilization of land resources. In essence, LUA optimization is a multi-objective optimization problem under the land use supply and demand constraints in a region. In order to obtain a better sustainable multi-objective LUA optimization solution, the present study proposes a LUA model based on the multi-objective artificial immune optimization algorithm (MOAIM-LUA model). The main achievements of the present study are as follows: (a) the land-use supply and demand factors are analyzed and the constraint conditions of LUA optimization problems are constructed based on the analysis framework of the balance between the land use supply and demand; (b) the optimization objectives of LUA optimization problems are defined and modeled using ecosystem service value theory and land rent and price theory; and (c) a multi-objective optimization algorithm is designed for solving multi-objective LUA optimization problems based on the novel immune clonal algorithm (NICA). On the basis of the aforementioned achievements, MOAIM-LUA was applied to a real case study of land-use planning in Anlu County, China. Compared to the current land use situation in Anlu County, optimized LUA solutions offer improvements in the social and ecological objective areas. Compared to the existing models, such as the non-dominated sorting genetic algorithm-II, experimental results demonstrate that the model designed in the present study can obtain better non-dominated solution sets and is superior in terms of algorithm stability.

Suggested Citation

  • Xiaoya Ma & Xiang Zhao, 2015. "Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China," Sustainability, MDPI, vol. 7(11), pages 1-20, November.
    • Handle: RePEc:gam:jsusta:v:7:y:2015:i:11:p:15632-15651:d:59278
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    2. Lijing Tang & Dongyan Wang, 2018. "Optimization of County-Level Land Resource Allocation through the Improvement of Allocation Efficiency from the Perspective of Sustainable Development," IJERPH, MDPI, vol. 15(12), pages 1-19, November.
    3. Dinghua Ou & Xingzhu Yao & Jianguo Xia & Xuesong Gao & Changquan Wang & Wanlu Chen & Qiquan Li & Zongda Hu & Juan Yang, 2019. "Development of a Composite Model for Simulating Landscape Pattern Optimization Allocation: A Case Study in the Longquanyi District of Chengdu City, Sichuan Province, China," Sustainability, MDPI, vol. 11(9), pages 1-35, May.
    4. Arjomandi, Amin & Mortazavi, Seyed Abolghasem & Khalilian, Sadegh & Garizi, Arash Zare, 2021. "Optimal land-use allocation using MCDM and SWAT for the Hablehroud Watershed, Iran," Land Use Policy, Elsevier, vol. 100(C).
    5. Xiang Zhao & Xiaoya Ma & Kun Wang & Yuqing Long & Dongjie Zhang & Zhanchun Xiao, 2017. "A Spatially Explicit Optimization Model for Agricultural Straw-Based Power Plant Site Selection: A Case Study in Hubei Province, China," Sustainability, MDPI, vol. 9(5), pages 1-19, May.

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