TY - GEN
T1 - Land use allocation optimization towards sustainable development based on genetic algorithm
AU - Kai, Cao
AU - Bo, Huang
AU - Qing, Zhao
AU - Shengxiao, Wang
PY - 2009
Y1 - 2009
N2 - An elitist genetic algorithm was used to find Pareto-optimal solutions for land use allocation with multiple objectives and constraints from the concepts of sustainable development. Plans were judged with regard to economic development, the environment and the social equality. A multi-objective fitness function was used. The genetic algorithm offers the possibility of efficiently searching over tens of thousands of plans for a tradeoff sets of non-dominated plans. In this research, the optimization includes not only the general objectives but also the spatial objectives focusing on the compactness, compatibility and accessibility. Further, I demonstrated a real world application of the model to land use allocation optimization in Tongzhou located in the east of Beijing. The results show that GA based land use allocation optimization is a promising and useful method for generating land use alternatives for further consideration in land use allocation decision-making.
AB - An elitist genetic algorithm was used to find Pareto-optimal solutions for land use allocation with multiple objectives and constraints from the concepts of sustainable development. Plans were judged with regard to economic development, the environment and the social equality. A multi-objective fitness function was used. The genetic algorithm offers the possibility of efficiently searching over tens of thousands of plans for a tradeoff sets of non-dominated plans. In this research, the optimization includes not only the general objectives but also the spatial objectives focusing on the compactness, compatibility and accessibility. Further, I demonstrated a real world application of the model to land use allocation optimization in Tongzhou located in the east of Beijing. The results show that GA based land use allocation optimization is a promising and useful method for generating land use alternatives for further consideration in land use allocation decision-making.
KW - Genetic algorithm
KW - Land use allocation optimization
KW - Pareto-optimal solutions
KW - Sustainable development
UR - https://www.scopus.com/pages/publications/74349095034
U2 - 10.1109/GEOINFORMATICS.2009.5292899
DO - 10.1109/GEOINFORMATICS.2009.5292899
M3 - 会议稿件
AN - SCOPUS:74349095034
SN - 9781424445639
T3 - 2009 17th International Conference on Geoinformatics, Geoinformatics 2009
BT - 2009 17th International Conference on Geoinformatics, Geoinformatics 2009
T2 - 2009 17th International Conference on Geoinformatics, Geoinformatics 2009
Y2 - 12 August 2009 through 14 August 2009
ER -
