Land use allocation optimization towards sustainable development based on genetic algorithm

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.