Simulating multi-objective spatial optimization allocation of land use based on the integration of multi-agent system and genetic algorithm

In this study, under the constraint of resource-saving and environment-friendliness objective, based on multi-agent genetic algorithm, multi-objective spatial optimization (MOSO) model for land use allocation was developed from the view of simulating the biological autonomous adaptability to environment and the competitive-cooperative relationship. The model was applied to solve the practical multi-objective spatial optimization allocation problems of land use in the core region of Changsha, Zhuzhou, Xiangttan city cluster in China. The results has indicated that MOSO model has much better performance than GA for solving complex multi-objective spatial optimization allocation problems and it is a promising method for generating land use alternatives for further consideration in spatial decision-making.