This study has developed the platform for Geographical Simulation and Optimization Systems (GeoSOS). The objective is to improve the limitations of current GIS on process analyses. GeoSOS consists of three major integrated components

cellular automata (CA)

multiagent systems (MAS)

and swarm intelligence (SI). This system is equipped with common CA algorithms

such as MCECA

LogisticCA

PCACA

ANNCA

and DecisiontreeCA. This system can automatically obtain transition rules according to data mining techniques. The incorporation of MAS and SI can help to solve a variety of complex geographical simulation and optimization problems. Another novelty of this proposed system is its capability of coupling simulation models with optimization models. Experiments have demonstrated that this coupling strategy can yield more satisfactory modeling results under complex changing environments.