多目标粒子群优化算法在配置城市土地使用上的应用Considering the ever-increasing urban population, it appears that land management is of major importance. Land uses must be properly arranged so that they do not interfere with one another and can meet each other’s needs as much as possible; this goal is a challenge of urban land-use planning. The main objective of this research is to use Multi-Objective Particle Swarm Optimization algorithm to find the optimum arrangement of urban land uses in parcel level, considering multiple objectives and constraints simultaneously. Geospatial Information System is used to prepare the data and to study different spatial scenarios when developing the model. To optimize the land-use arrangement, four objectives are defined: maximizing compatibility, maximizing dependency, maximizing suitability, and maximizing compactness of land uses. These objectives are characterized based on the requirements of planners. As a result of optimization, the user is provided with a set of optimum land-use arrangements, the Pareto-front solutions. The user can select the most appropriate solutions according to his/her priorities. The method was tested using the data of region 7, district 1 of Tehran. The results showed an acceptable level of repeatability and stability for the optimization algorithm. The model uses parcel instead of urban blocks, as the spatial unit.Moreover, it considers a variety of land uses and tries to optimize several objectives Simultaneously.1 摘要：考虑到不断增加的城市人口，土地管理看起来就具有重大意义。土地利用必须妥善安排，使它们不会干扰彼此并尽可能满足对方的需要；这个目标对于城市土地利用规划是一个挑战。本讨论的主要目的是同时考虑多个目标限制，利用多目标粒子群优化算法来找到最佳用于城市土地安排地块的水平。地理空...
