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

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

Ecological Modelling, 2016, vol. 320, issue C, 334-347

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.

Keywords: Land use allocation; Multi-objective optimization; Multi-agent system; Sustainable land use; China (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (18)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:320:y:2016:i:c:p:334-347

DOI: 10.1016/j.ecolmodel.2015.10.017

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