Abstract
Although being increasingly powerful in handling spatial data, geographical information systems (GIS) still lack the powerful functionality for process modeling in terms of simulation and optimization. This article discusses the concepts and methodologies of a geographical simulation and optimization system (GeoSOS). GeoSOS integrates cellular automata (CA), agent-based models (ABMs), and swarm intelligence models (SIMs) for solving process simulation and optimization problems. A general form of the so-called interaction rules is proposed for implementing this integrated system. The GeoSOS software is developed to provide these complementary functions that are unavailable in the current GIS. Experiments have demonstrated that GeoSOS is able to model the reciprocal relationships between urban simulation and spatial optimization (e.g., facility sitting, transport development, and natural protection) in fast-growing regions. Better modeling performances have been achieved using the coupling strategies of GeoSOS.
| Original language | English |
|---|---|
| Pages (from-to) | 633-655 |
| Number of pages | 23 |
| Journal | International Journal of Geographical Information Science |
| Volume | 25 |
| Issue number | 4 |
| DOIs | |
| State | Published - Apr 2011 |
| Externally published | Yes |
Keywords
- Agent-based models
- Cellular automata
- GeoSOS
- Spatial optimization
- Swarm intelligence
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