Concepts, methodologies, and tools of an integrated geographical simulation and optimization system

Authored by Xia Li, Xiaoping Liu, Jinqiang He, Yimin Chen, Dan Li

Date Published: 2011

DOI: 10.1080/13658816.2010.496370

Sponsors: Chinese National Natural Science Foundation Key National Natural Science Foundation of China National Outstanding Youth Foundation of China

Platforms: .NET

Model Documentation: UML Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

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.

Tags

Agent-based models Swarm intelligence Cellular automata Spatial optimization GeoSOS