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Simulating multi-objective land use optimization allocation using Multi-agent system—A case study in Changsha, China

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  • Zhang, Honghui
  • Zeng, Yongnian
  • Jin, Xiaobin
  • Shu, Bangrong
  • Zhou, Yinkang
  • Yang, Xuhong

Abstract

Achieving multi-objective land use optimization allocation (MOLUOA) for sustainable development is an important issue in land use. In consideration of the multi-dimensional characteristics of MOLUOA in terms of quantity, space, and time, and under the constraints of maximizing economic, ecological, and social benefits of land use, a MOLUOA model is developed in this study by integrating multi-agent system with particle swarm optimization. The MOLUOA model is applied to the simulation of land use optimization allocation in Changsha, a typical city located in central China. Simulation results show that the MOLUOA model can achieve multi-objective land use optimization allocation in terms of quantity, space, and time. The model can provide decision-making support for generating land use alternatives to achieve sustainable land use.

Suggested Citation

  • Zhang, Honghui & Zeng, Yongnian & Jin, Xiaobin & Shu, Bangrong & Zhou, Yinkang & Yang, Xuhong, 2016. "Simulating multi-objective land use optimization allocation using Multi-agent system—A case study in Changsha, China," Ecological Modelling, Elsevier, vol. 320(C), pages 334-347.
    • Handle: RePEc:eee:ecomod:v:320:y:2016:i:c:p:334-347
    DOI: 10.1016/j.ecolmodel.2015.10.017
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    12. Tian, Fenghao & Li, Mingyu & Han, Xulong & Liu, Hui & Mo, Boxian, 2020. "A Production–Living–Ecological Space Model for Land-Use Optimisation: A case study of the core Tumen River region in China," Ecological Modelling, Elsevier, vol. 437(C).
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