Abstract
Human migration plays an important role in the city spatial evolution. This paper presents a new simulation model of city spatial evolution that explicitly considers preference and exploration in the migration choice decision process. In the model, the preference means that human prefer to move to the communities which have more people, while the exploration implies that human wish to explore the unknown communities randomly. By introducing the carrying capacity (CC), maximum movement distance (MMD), migration rate (MR) and random migration parameter (RMP), we investigate the effects of them on the city spatial distribution. All of the parameters can govern how many people can live in each community, how far people can explore and how many people move per time step, etc. A numerical simulation experiment is presented to illustrate that the form of the city is centralized with the increase of CC, MMD and MR, while it will be decentralized as the RMP grows.
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