Genetic Algorithm Design in Urban Spatial Growth Modeling

In order to reflect the dynamic, multi-objective and non-linear features and provide stronger decision-making support for urban spatial growth, this paper explores methods and technical route using genetic algorithm in urban spatial growth model, including encoding used for expressing urban growth individual, initial cluster setting for genetic algorithm operation beginning, fitness function design for evaluating individual strengths and weaknesses and implementation of the necessary constraints, then outlines the process of genetic algorithm operation, and makes appropriate statements about GIS techniques supporting genetic algorithm realization.