A grey wolf optimizer-cellular automata integrated model for urban growth simulation and optimization: GWO-CA integrated model for urban growth

Journal: 《Transactions in GIS》

Cite as: Cao M, Huang M, Xu R, Lü G, Chen M. A grey wolf optimizer–cellular automata integrated model for urban growth simulation and optimization. Transactions in GIS. 2018;00:1–16. https://doi.org/10.1111/tgis.12517

Abstract: This article proposes a grey wolf optimizer (GWO) and cel‐lular automata (CA) integrated model for the simulation and spatial optimization of urban growth. A new grey wolf‐inspired approach is put forward to determine the urban growth rules of CA cells by using the GWO algorithm, which is suitable for solving optimization problems. The inspiration for GWO comes from the social leadership of wolf groups, as well as their hunting behavior. The GWO‐optimized urban growth rules for CA describe the relation‐ship between the spatial variables and the urban land‐use status for each cell in the formation of “if–then.” The GWO algorithm and CA model are then integrated as the GWO–CA model for urban growth simulation and optimization. By taking Nanjing City as an example, the simulation ac‐curacy in terms of urban cells is 86.6%, and the kappa co‐efficient is 0.715, indicating that the GWO algorithm is efficient at obtaining urban growth rules from spatial vari‐ables. The validation of the GWO–CA model also illus‐trates that it performs well in terms of the simulation and spatial optimization of urban growth, and can further con‐tribute to urban planning and management.